Biomarkers for the diagnosis of lacunar stroke

ABSTRACT

This invention provides gene expression profiles useful for diagnosing lacunar stroke and for distinguishing lacunar stroke from non-lacunar stroke.

CROSS-REFERENCE TO RELATED APPLICATIONS

This application is a divisional of U.S. application Ser. No.13/410,025, filed on Mar. 1, 2012, which claims the benefit of U.S.Provisional Application No. 61/449,347, filed on Mar. 4, 2011, which arehereby incorporated herein in their entireties for all purposes.

STATEMENT OF GOVERNMENTAL SUPPORT

This work was supported in part by Grant No NS056302, awarded by theNational Institutes of Health and National Institute of NeurologicalDisorders and Stroke (NINDS). The Government has certain rights in thisinvention.

FIELD OF THE INVENTION

The present invention relates to expression profiling to differentiatestroke of lacunar etiology from non-lacunar stroke.

BACKGROUND OF THE INVENTION

Small deep infarcts (SDI) including lacunar stroke account for greaterthan one quarter of all ischemic strokes. Though SDI cause the smallestamount of brain injury of all stroke subtypes, long-term outcomes aresignificant with 42% of lacunar stroke patients being dependent by 3years (Samuelsson et al., Stroke (1996) 27(5):842-6; Lee, et al., Int JCardiol. (2009) Mar. 25; Giroud, et al, Rev Neurol (Paris). (1991)147(8-9):566-72; Clavier, et al., Stroke. (1994) 25(10):2005-9;Carod-Artal, et al., Stroke. (2005) 36(5):965-70). Indeed, lacunarstrokes are indicative of cardiovascular disease with an annual deathrate of 2.8% and an increased risk of recurrent stroke, white matterdisease and cognitive impairment (Samuelsson, et al., supra; Norrving,Lancet Neurol. (2003) 2(4):238-45; Jackson, et al., Brain. (2005) 128(Pt11):2507-17).

The term lacune was first used to describe small subcortical infarctionsin the 1800s by Dechambre and Durand-Fardel. In the 1960s Miller Fisherdescribed the lacunar hypothesis, correlating the clinical symptoms oflacunar syndromes with pathologic findings of single perforating branchocclusion from microatheroma or lipohyalinosis (Fisher, ActaNeuropathol. (1968) 12(1):1-15; Fisher, Neurology (1965) 15:774-84;Fisher, Neurology (1982) 32(8):871-6; and Bamford and Warlow, Stroke.(1988) 19(9):1074-82). The lacunar hypothesis distinguishes lacunarstroke from other causes of SDI, including disease of the parent arteryand embolism of arterial or cardiac origin. Determining whether an SDIis of small vessel lacunar or non-small vessel etiology remains a topicof controversy and investigation (Millikan, et al., Stroke (1990)21(9):1251-7; Futrell, Stroke (2004) 35(7):1778-9; Norrving, Stroke(2004) 35(7):1779-80; Davis and Donnan, Stroke (2004) 35(7):1780-1; andMaron, et al., J Am Coll Cardiol. (2002) 39(2):301-7). An embolic causeof stroke warrants a different investigative strategy and treatment thanother ischemic stroke syndromes. In particular, it is important todiagnose disease that would change management, such as carotid surgeryfor symptomatic carotid stenosis and warfarin for symptomatic atrialfibrillation. Therefore, ascertaining the etiology of SDI is not only ofacademic interest but also of clinical significance.

The presence of a potential cardioembolic or arterial embolic sourcedoes not necessarily imply a causal association with SDI. Indeed, mostof the vascular risk factors associated with lacunar infarction are alsothose that predispose to arterial and cardioembolic disease. Severalpredictors have been identified to suggest an SDI is of lacunaretiology. The clinical features of a lacunar syndrome predict infarctsthat are radiological findings consistent with lacunar stroke (Gan, etal., Neurology (1997) 48(5):1204-11; and Lee, et al., Stroke (2005)36(12):2583-8). However, lacunar syndromes can be mimicked bynon-lacunar disease, such as cortical infarction, hemorrhagic stroke andnon-vascular disease (Wessels, et al., Stroke (2005) 36(4):757-61;Arboix, et al., BMC Neurol. (2010) 10:31). Furthermore, infarction inthe regions of the penetrating arteries (basal ganglia, thalamus,internal capsule, corona radiata and pons) can result from non-lacunardisease, including disease of the parent artery and emboli of arterialor cardiac origin. Infarct diameter<15 mm is also predictive of lacunarstroke, since this is the approximate vascular territory of a singlepenetrating artery (Bang, et al., Cerebrovasc Dis. (2007) 24(6):520-9;Cho, et al., Cerebrovasc Dis. (2007) 23(1):14-9; and Lodder, CerebrovascDis. (2007) 24(1):156-7). However, in patients with SDI>15 mm in size orwith a coincidental arterial or cardioembolic source, it remains lessclear as to whether a stroke is of lacunar or non-lacunar etiology.

The present invention is based, in part, on using gene expressionprofiling to distinguish patients who have suffered or are at risk ofsuffering lacunar stroke from patients who have suffered or are at riskof suffering embolic strokes using a gene expression profiling. The geneexpression profiles further find use to predict the cause of stroke inSDI of unclear cause (SDI size>15 mm or SDI with potential embolicsource). It has recently been demonstrated that cardioembolic and largevessel causes of stroke have unique gene expression signatures(Jickling, et al., Ann Neurol. (2010) 68(5):681-92; and Xu, et al., JCereb Blood Flow Metab. (2008) 28(7):1320-8). These signatures can beused to categorize, diagnose and treat stroke patients by cause based ona profile of differentially expressed genes. The identified genes werepredominantly expressed in inflammatory cells associated with eachstroke subtype. The present invention is based, in part, on theidentification of a profile of differentially expressed genes useful todistinguish lacunar stroke from non-lacunar stroke and to predictetiology in SDI of unclear cause.

SUMMARY OF THE INVENTION

The present invention provides biomarker useful for diagnosing theoccurrence or risk of lacunar stroke and for distinguishing theoccurrence or risk of lacunar stroke from non-lacunar stroke.Accordingly, in one aspect, the invention provides methods fordiagnosing the occurrence of lacunar stroke or a predisposition forexperiencing lacunar stroke. In some embodiments, the methods comprise:

a) determining a level of expression of a plurality of lacunarstroke-associated biomarkers in a biological sample from a patient,wherein the biomarkers are selected from Table 3; and

b) comparing the level of expression of the lacunar stroke-associatedbiomarkers to the expression level of a plurality of stably expressedendogenous reference biomarkers;

wherein an increase of the expression level of one or more biomarkersselected from the group consisting of RASEF, CALM1, TTC12, CCL3, CCL3L1,CCL3L3, CCDC78, PRSS23, LAIR2, C18orf49, UTS2, LGR6, PROCR, LAG3, OASL,LOC100132181, HLA-DRB4, CCL2, ALS2CR11, SCAND2, GBP4, RUNX3, TSEN54,UBA7, FAM179A, TGFBR3, CCDC114, AKAP9, BNC2, BZRAP1, CCL4, CHST2, CSF1,ERBB2, GBR56, GRAMD3, GRHL2, GRK4, ITIH4, KIAA1618, LOC147646,LOC150622, LOC161527, PLEKHF1, PRKD2, RGNEF, SESN2, SLAMF7, SPON2,STAT1, SYNGR1, TRX21, TMEM67, TUBE1, and ZNF827, and/or a decrease ofthe expression level of one or more biomarkers selected from the groupconsisting of HLA-DQA1, FLJ13773, QKI, MPZL3, FAM70B, LOC254128, IL8,CHML, STX7, VAPA, UGCG, PDXDC1, LRRC8B, STK4, GTF2H2, AGFG1, BTG1,CFDP1, CNPY2, FAM105A, GATM, GTF2H2B, IGHG1, IL18RAP, N4BP2, PHACTR1,RTKN2, SLC16A1, SOCS1, SPAG17, ST6GALNAC1, STK17B, STT3B, STX16,TBC1D12, TRIM4, UACA, and WHAMML2 compared to the expression level ofthe plurality of endogenous reference biomarkers is correlative with orindicates that the patient suffers from or is at risk of experiencinglacunar stroke, thereby diagnosing the occurrence of lacunar stroke orthe predisposition for experiencing lacunar stroke.

In a related aspect, the invention provides methods for distinguishingthe occurrence of lacunar stroke or a predisposition for experiencinglacunar stroke from the occurrence of non-lacunar stroke or apredisposition for experiencing non-lacunar stroke. In some embodiments,the methods comprise:

a) determining a level of expression of a plurality of lacunarstroke-associated biomarkers in a biological sample from a patient,wherein the biomarkers are selected from Table 3; and

b) comparing the level of expression of the lacunar stroke-associatedbiomarkers to the expression level of a plurality of stably expressedendogenous reference biomarkers;

wherein an increase of the expression level of one or more biomarkersselected from the group consisting of RASEF, CALM1, TTC12, CCL3, CCL3L1,CCL3L3, CCDC78, PRSS23, LAIR2, C18orf49, UTS2, LGR6, PROCR, LAG3, OASL,LOC100132181, HLA-DRB4, CCL2, ALS2CR11, SCAND2, GBP4, RUNX3, TSEN54,UBA7, FAM179A, TGFBR3, CCDC114, AKAP9, BNC2, BZRAP1, CCL4, CHST2, CSF1,ERBB2, GBR56, GRAMD3, GRHL2, GRK4, ITIH4, KIAA1618, LOC147646,LOC150622, LOC161527, PLEKHF1, PRKD2, RGNEF, SESN2, SLAMF7, SPON2,STAT1, SYNGR1, TRX21, TMEM67, TUBE1, and ZNF827, and/or a decrease ofthe expression level of one or more biomarkers selected from the groupconsisting of HLA-DQA1, FLJ13773, QKI, MPZL3, FAM70B, LOC254128, IL8,CHML, STX7, VAPA, UGCG, PDXDC1, LRRC8B, STK4, GTF2H2, AGFG1, BTG1,CFDP1, CNPY2, FAM105A, GATM, GTF2H2B, IGHG1, IL18RAP, N4BP2, PHACTR1,RTKN2, SLC16A1, SOCS1, SPAG17, ST6GALNAC1, STK17B, STT3B, STX16,TBC1D12, TRIM4, UACA, and WHAMML2 compared to the expression level ofthe plurality of endogenous reference biomarkers is correlative with orindicates that the patient suffers from or is at risk of experiencinglacunar stroke; and/or

wherein a decrease of the expression level of one or more biomarkersselected from the group consisting of RASEF, CALM1, TTC12, CCL3, CCL3L1,CCL3L3, CCDC78, PRSS23, LAIR2, C18orf49, UTS2, LGR6, PROCR, LAG3, OASL,LOC100132181, HLA-DRB4, CCL2, ALS2CR11, SCAND2, GBP4, RUNX3, TSEN54,UBA7, FAM179A, TGFBR3, CCDC114, AKAP9, BNC2, BZRAP1, CCL4, CHST2, CSF1,ERBB2, GBR56, GRAMD3, GRHL2, GRK4, ITIH4, KIAA1618, LOC147646,LOC150622, LOC161527, PLEKHF1, PRKD2, RGNEF, SESN2, SLAMF7, SPON2,STAT1, SYNGR1, TRX21, TMEM67, TUBE1, and ZNF827, and an increase of theexpression level of one or more biomarkers selected from the groupconsisting of HLA-DQA1, FLJ13773, QKI, MPZL3, FAM70B, LOC254128, IL8,CHML, STX7, VAPA, UGCG, PDXDC1, LRRC8B, STK4, GTF2H2, AGFG1, BTG1,CFDP1, CNPY2, FAM105A, GATM, GTF2H2B, IGHG1, IL18RAP, N4BP2, PHACTR1,RTKN2, SLC16A1, SOCS1, SPAG17, ST6GALNAC1, STK17B, STT3B, STX16,TBC1D12, TRIM4, UACA, and WHAMML2 compared to the expression level ofthe plurality of endogenous reference biomarkers is correlative with orindicates that the patient suffers from or is at risk of experiencingnon-lacunar stroke;

thereby distinguishing the occurrence of lacunar stroke or thepredisposition for experiencing lacunar stroke from the occurrence ofnon-lacunar stroke or a predisposition for experiencing non-lacunarstroke.

In a related aspect, the invention provides methods for diagnosinglacunar stroke or a predisposition for developing lacunar stroke. Insome embodiments, the methods comprise determining a level of expressionof a plurality of lacunar stroke-associated biomarkers in a biologicalsample from a patient, wherein an increase or decrease of the levelcompared to a control level is correlative with or indicates that thepatient suffers from or is at risk of developing lacunar stroke;

wherein an increase of the expression level of one or more biomarkersselected from the group consisting of RASEF, CALM1, TTC12, CCL3, CCL3L1,CCL3L3, CCDC78, PRSS23, LAIR2, C18orf49, UTS2, LGR6, PROCR, LAG3, OASL,LOC100132181, HLA-DRB4, CCL2, ALS2CR11, SCAND2, GBP4, RUNX3, TSEN54,UBA7, FAM179A, TGFBR3, CCDC114, AKAP9, BNC2, BZRAP1, CCL4, CHST2, CSF1,ERBB2, GBR56, GRAMD3, GRHL2, GRK4, ITIH4, KIAA1618, LOC147646,LOC150622, LOC161527, PLEKHF1, PRKD2, RGNEF, SESN2, SLAMF7, SPON2,STAT1, SYNGR1, TRX21, TMEM67, TUBE1, and ZNF827, and/or a decrease ofthe expression level of one or more biomarkers selected from the groupconsisting of HLA-DQA1, FLJ13773, QKI, MPZL3, FAM70B, LOC254128, IL8,CHML, STX7, VAPA, UGCG, PDXDC1, LRRC8B, STK4, GTF2H2, AGFG1, BTG1,CFDP1, CNPY2, FAM105A, GATM, GTF2H2B, IGHG1, IL18RAP, N4BP2, PHACTR1,RTKN2, SLC16A1, SOCS1, SPAG17, ST6GALNAC1, STK17B, STT3B, STX16,TBC1D12, TRIM4, UACA, and WHAMML2 compared to the control level iscorrelative with or indicates that the patient suffers from or is atrisk of experiencing lacunar stroke, thereby diagnosing the occurrenceof lacunar stroke or the predisposition for experiencing lacunar stroke.In some embodiments, the control is the expression level of one or morestably expressed endogenous reference biomarkers.

With respect to the embodiments, in some embodiments, an increase of theexpression level of one or more biomarkers selected from the groupconsisting of RASEF, CALM1, TTC12, CCL3, CCL3L1, CCL3L3, CCDC78, PRSS23,LAIR2, C18orf49, UTS2, LGR6, PROCR, LAG3, OASL, LOC100132181, HLA-DRB4,CCL2, ALS2CR11, SCAND2, GBP4, RUNX3, TSEN54, UBA7, FAM179A, TGFBR3 andCCDC114, and/or a decrease of the expression level of one or morebiomarkers selected from the group consisting of HLA-DQA1, FLJ13773,QKI, MPZL3, FAM70B, LOC254128, L8, CHML, STX7, VAPA, UGCG, PDXDC1,LRRC8B, STK4, GTF2H2, compared to the expression level of the pluralityof endogenous reference biomarkers is correlative with or indicates thatthe patient suffers from or is at risk of experiencing lacunar stroke.In some embodiments, a decrease of the expression level of one or morebiomarkers selected from the group consisting of RASEF, CALM1, TTC12,CCL3, CCL3L1, CCL3L3, CCDC78, PRSS23, LAIR2, C18orf49, UTS2, LGR6,PROCR, LAG3, OASL, LOC100132181, HLA-DRB4, CCL2, ALS2CR11, SCAND2, GBP4,RUNX3, TSEN54, UBA7, FAM179A, TGFBR3 and CCDC114, and an increase of theexpression level of one or more biomarkers selected from the groupconsisting of HLA-DQA1, FLJ13773, QKI, MPZL3, FAM70B, LOC254128, L8,CHML, STX7, VAPA, UGCG, PDXDC1, LRRC8B, STK4, GTF2H2, compared to theexpression level of the plurality of endogenous reference biomarkers iscorrelative with or indicates that the patient suffers from or is atrisk of experiencing non-lacunar stroke.

In some embodiments, an increase of the expression level of one or morebiomarkers selected from the group consisting of RASEF, CALM1, TTC12,CCL3, CCL3L1, CCL3L3, CCDC78, PRSS23, LAIR2, C18orf49, UTS2, LGR6,PROCR, LAG3, OASL, LOC100132181, HLA-DRB4, CCL2, and ALS2CR11, and/or adecrease of the expression level of one or more biomarkers selected fromthe group consisting of HLA-DQA1, FLJ13773, QKI, MPZL3, FAM70B,LOC254128, IL8, CHML, STX7, VAPA, UGCG, and PDXDC1, compared to theexpression level of the plurality of endogenous reference biomarkers iscorrelative with or indicates that the patient suffers from or is atrisk of experiencing lacunar stroke. In some embodiments, a decrease ofthe expression level of one or more biomarkers selected from the groupconsisting of RASEF, CALM1, TTC12, CCL3, CCL3L1, CCL3L3, CCDC78, PRSS23,LAIR2, C18orf49, UTS2, LGR6, PROCR, LAG3, OASL, LOC100132181, HLA-DRB4,CCL2, and ALS2CR11, and an increase of the expression level of one ormore biomarkers selected from the group consisting of HLA-DQA1,FLJ13773, QKI, MPZL3, FAM70B, LOC254128, L8, CHML, STX7, VAPA, UGCG, andPDXDC1, compared to the expression level of the plurality of endogenousreference biomarkers is correlative with or indicates that the patientsuffers from or is at risk of experiencing non-lacunar stroke.

In some embodiments, an increase of the expression level of one or morebiomarkers selected from the group consisting of RASEF, CALM1, TTC12,CCL3, CCL3L1, CCL3L3, CCDC78, PRSS23, LAIR2, C18orf49, UTS2, and LGR6,and/or a decrease of the expression level of one or more biomarkersselected from the group consisting of HLA-DQA1, FLJ13773, QKI, MPZL3,FAM70B, LOC254128, L8, CHML, and STX7, compared to the expression levelof the plurality of endogenous reference biomarkers is correlative withor indicates that the patient suffers from or is at risk of experiencinglacunar stroke. In some embodiments, a decrease of the expression levelof one or more biomarkers selected from the group consisting of RASEF,CALM1, TTC12, CCL3, CCL3L1, CCL3L3, CCDC78, PRSS23, LAIR2, C18orf49,UTS2, LGR6, and PROCR, and an increase of the expression level of one ormore biomarkers selected from the group consisting of HLA-DQA1,FLJ13773, QKI, MPZL3, FAM70B, LOC254128, IL8, CHML, and STX7, comparedto the expression level of the plurality of endogenous referencebiomarkers is correlative with or indicates that the patient suffersfrom or is at risk of experiencing non-lacunar stroke.

In some embodiments, an increase of the expression level of one or morebiomarkers selected from the group consisting of RASEF, CALM1, TTC12,CCL3, CCL3L1, CCL3L3, CCDC78, PRSS23, and LAIR2, and/or a decrease ofthe expression level of one or more biomarkers selected from the groupconsisting of HLA-DQA1, FLJ13773, and QKI, compared to the expressionlevel of the plurality of endogenous reference biomarkers is correlativewith or indicates that the patient suffers from or is at risk ofexperiencing lacunar stroke. In some embodiments, a decrease of theexpression level of one or more biomarkers selected from the groupconsisting of RASEF, CALM1, TTC12, CCL3, CCL3L1, CCL3L3, CCDC78, PRSS23,and LAIR2, and an increase of the expression level of one or morebiomarkers selected from the group consisting of HLA-DQA1, FLJ13773, andQKI, compared to the expression level of the plurality of endogenousreference biomarkers is correlative with or indicates that the patientsuffers from or is at risk of experiencing non-lacunar stroke.

In various embodiments, the expression levels of the biomarkers areconcurrently or sequentially determined.

In some embodiments, the methods further comprise the step of obtaininga biological sample from the patient. In some embodiments, thebiological sample is blood, serum or plasma.

In some embodiments, the method is performed in a clinical laboratory.In some embodiments, the method is performed at the point of care.

In some embodiments, the plurality of stably expressed endogenousreference biomarkers are selected from USP7, MAPRE2, CSNK1G2, SAFB2,PRKAR2A, PI4 KB, CRTC1, HADHA, MAP1LC3B, KAT5, GTSE1, CDC2L1///CDC2L2,TCF25, CHP, LRRC40, hCG_2003956///LYPLA2///LYPLA2P1, DAXX, UBE2NL, EIF1,KCMF1, PRKRIP1, CHMP4A, TMEM184C, TINF2, PODNL1, FBXO42, LOC441258,RRP1, C10orf104, ZDHHC5, C9orf23, LRRC45, NACC1,LOC100133445///LOC115110 and PEX16. In some embodiments, the lacunarstroke-associated biomarkers are overexpressed or underexpressed atleast about 1.2-fold, 1.3-fold, 1.4-fold, 1.5-fold, 1.6-fold, 1.7-fold,1.8-fold, 1.9-fold, 2.0-fold, 2.1 fold, 2.2-fold, 2.3-fold, 2.4-fold,2.5-fold, 2.6-fold, 2.7-fold, 2.8-fold, 2.9-fold, 3.0-fold, or more, incomparison to the expression levels of a plurality of stably expressedendogenous reference biomarkers. In some embodiments, the expressionlevels of 2, 3, 4, 5, 6, 7, 8, 9, 10, 15, 20, 25, 30, 35, or all, theendogenous reference biomarkers selected from the group consisting ofUSP7, MAPRE2, CSNK1G2, SAFB2, PRKAR2A, PI4KB, CRTC1, HADHA, MAP1LC3B,KAT5, CDC2L1///CDC2L2, GTSE1, CDC2L1///CDC2L2, TCF25, CHP, LRRC40,hCG_2003956///LYPLA2///LYPLA2P1, DAXX, UBE2NL, EIF1, KCMF1, PRKRIP1,CHMP4A, TMEM184C, TINF2, PODNL1, FBXO42, LOC441258, RRP1, C10orf104,ZDHHC5, C9orf23, LRRC45, NACC1, LOC100133445///LOC115110, PEX16 aredetermined as a control.

In some embodiments, the level of expression of about 15-85, 20-70,30-60 or 40-50 lacunar stroke-associated biomarkers are determined. Insome embodiments, about 15, 20, 25, 30, 35, 40, 45, 50, 55, 60, 65, 70,75, 80, 85, 90, 95 or 100 lacunar stroke-associated biomarkers aredetermined. In some embodiments, the expression levels of at least about3, 5, 10, 15, 20, 25, 30 or more lacunar stroke-associated biomarkersfrom Table 3 are determined. In some embodiments, the expression levelsof at least about 3, 5, 10, 15, 20, 25, 30 or more lacunarstroke-associated biomarkers from Table 4 are determined.

In some embodiments, the determining step is performed within 72 hours,for example, within 60 hours, 48 hours, 36 hours, 24 hours, 12 hours, 6hours or 3 hours, after a suspected ischemic event.

In some embodiments, the patient is asymptomatic. In some embodiments,the patient is exhibiting symptoms of ischemic stroke, e.g., of havingexperienced an ischemic event, of experiencing an ischemic event, or ofan imminent ischemic event. In some embodiments, the patient hassuffered an ischemic event. In some embodiments, the determining step isperformed at 3 or fewer hours after the ischemic event. In someembodiments, the determining step is performed 3 or more hours after theischemic event.

In some embodiments, the patient has at least one vascular risk factor.In some embodiments, the patient has experienced a small deep infarction(SDI). In some embodiments, the patient shows evidence ofmicrohemorrhage. In some embodiments, the patient is non-Caucasian. Insome embodiments, the patient does not have arterial disease ipsilateralto the stroke.

In various embodiments, the methods, particularly performance of thecomparison step, are computer implemented. Such computer-implementedmethods may also provide an output of the comparison of expressionlevels.

Methods for determining the occurrence or predisposition of a lacunarstroke may further comprise the step of determining whether the patienthas suffered a myocardial infarction or whether the patient has vascularrisk factors. Methods for determining the occurrence or predispositionof a lacunar stroke may further comprise the step of determining whetherthe patient has evidence of microhemorrhage or whether the patient hasarterial disease or whether the patient has cerebral vascular disease.Methods for determining the occurrence or predisposition of a lacunarstroke may further comprise the step of determining whether the patienthas suffered a small deep infarction (SDI).

In some embodiments, the level of expression of the biomarker isdetermined at the transcriptional level. In some embodiments, the levelof expression is determined by detecting hybridization of a lacunarstroke-associated gene probe to gene transcripts of the biomarkers inthe biological sample.

In some embodiments, the methods further comprise the step of performingadditional diagnostic tests useful for identifying whether a patient hasexperienced or has a predisposition to experience lacunar stroke, e.g.,based on imaging or ultrasound techniques. In various embodiments, themethods further comprise performing one or more diagnostic testsselected from the group consisting of X-ray computed tomography (CT),magnetic resonance imaging (MRI) brain scanning, vascular imaging of thehead and neck with doppler or magnetic resonance angiography (MRA), CTangiography (CTA), electrocardiogram (e.g., EKG or ECG), cardiacultrasound and cardiac monitoring. In various embodiments, the patientis subjected to cardiac monitoring for at least 2 days, e.g., for 2-30days or for 7-21 days, e.g., for 2, 5, 7, 10, 12, 14, 18, 20, 21, 25,28, 30, or more days, as appropriate. In various embodiments, thelocation of the infarction is determined. An infarction located in asubcortical region of the brain is associated with or correlated with adiagnosis of lacunar stroke. An infarction located in a cortical regionof the brain, e.g., in regions of the penetrating arteries, e.g., basalganglia, thalamus, internal capsule, corona radiata and/or pons, isassociated with or correlated with a diagnosis of non-lacunar stroke. Insome embodiments, the size of the infarction is determined.

In some embodiments, the methods further comprise the step ofrecommending or providing a regime of treatment to the patientappropriate to the determined cause of stroke. For example, in patientsdiagnosed as experiencing or having a predisposition for experiencinglacunar stroke, the methods further provide for recommending orproviding a regime of treatment or prevention for lacunar stroke.

In various embodiments, the methods may further comprise the step ofdetermining the cause or risk of ischemic stroke if the patient hasexperienced or has a predisposition to experience non-lacunar stroke.The methods may further comprise the step of recommending or providing aregime of treatment to the patient appropriate to the determined causeof non-lacunar stroke. For example, in patients diagnosed asexperiencing or having a predisposition for experiencing cardioembolicstroke, the methods further provide for recommending or providing aregime of treatment or prevention for cardioembolic stroke. In patientsdiagnosed as experiencing or having a predisposition for experiencingcarotid stenosis, the methods further provide for recommending orproviding a regime of treatment or prevention for carotid stenosis. Inpatients diagnosed as experiencing or having a predisposition forexperiencing atrial fibrillation, the methods further provide forrecommending or providing a regime of treatment or prevention for atrialfibrillation. In patients diagnosed as experiencing or having apredisposition for experiencing transient ischemic attack, the methodsfurther provide for recommending or providing a regime of treatment orprevention for transient ischemic attack.

With respect to embodiments for determination of the level of expressionof the biomarkers, in some embodiments, the level of expression of thebiomarker is determined at the transcriptional level. For example, insome embodiments, the level of expression is determined by detectinghybridization of an ischemic stroke-associated gene probe to genetranscripts of the biomarkers in the biological sample. In someembodiments, the hybridization step is performed on a nucleic acid arraychip. In some embodiments, the hybridization step is performed in amicrofluidics assay plate. In some embodiments, the level of expressionis determined by amplification of gene transcripts of the biomarkers. Insome embodiments, the amplification reaction is a polymerase chainreaction (PCR).

In some embodiments, the level of expression of the biomarker isdetermined at the protein level.

In a further aspect, the invention provides a solid support comprising aplurality of nucleic acids that hybridize to a plurality of lacunarstroke-associated genes selected from the group consisting of HLA-DQA1,FLJ13773, RASEF, CALM1, QKI, TTC12, CCL3///CCL3L1///CCL3L3, CCDC78,PRSS23, LAIR2, C18orf49, MPZL3, UTS2, FAM70B, UTS2, LOC254128, LGR6,IL8, CHML, STX7, PROCR, VAPA, LAG3, OASL, LOC100132181, HLA-DRB4, CCL2,UGCG, PDXDC1, ALS2CR11, SCAND2, GBP4, RUNX3, LRRC8B, TSEN54, UBA7, STK4,FAM179A, TGFBR3, CCDC114, GTF2H2, AKAP9, BNC2, BZRAP1, CCL4, CHST2,CSF1, ERBB2, GBR56, GRAMD3, GRHL2, GRK4, ITIH4, KIAA1618, LOC147646,LOC150622, LOC161527, PLEKHF1, PRKD2, RGNEF, SESN2, SLAMF7, SPON2,STAT1, SYNGR1, TRX21, TMEM67, TUBE1, ZNF827, AGFG1, BTG1, CFDP1, CNPY2,FAM105A, GATM, GTF2H2, IGHG1, IL18RAP, N4BP2, PHACTR1, QK1, RTKN2,SLC16A1, SOCS1, SPAG17, ST6GALNAC1, STK17B, STT3B, STX16, TBC1D12,TRIM4, UACA, and WHAMML2. As appropriate, the solid support maycomprise, 2, 5, 10, 15, 20, 25, 30, 35, 40, 45, 50, 55, 60, 65, 70, 75,80, 85, 90, 95 or more, nucleic acids that hybridize to a plurality oflacunar stroke-associated genes. The solid support may be provided in akit.

In some embodiments, the solid support comprises a plurality of nucleicacids that hybridize to a plurality of lacunar stroke-associated genesselected from the group consisting of HLA-DQA1, FLJ13773, RASEF, CALM1,QKI, TTC12, CCL3///CCL3L1///CCL3L3, CCDC78, PRSS23, LAIR2, C18orf49,MPZL3, UTS2, FAM70B, UTS2, LOC254128, LGR6, IL8, CHML, STX7, PROCR,VAPA, LAG3, OASL, LOC100132181, HLA-DRB4, CCL2, UGCG, PDXDC1, ALS2CR11,SCAND2, GBP4, RUNX3, LRRC8B, TSEN54, UBA7, STK4, FAM179A, TGFBR3,CCDC114 and GTF2H2.

In some embodiments, the solid support comprises a plurality of nucleicacids that hybridize to a plurality of lacunar stroke-associated genesselected from the group consisting of HLA-DQA1, FLJ13773, RASEF, CALM1,QKI, TTC12, CCL3///CCL3L1///CCL3L3, CCDC78, PRSS23, LAIR2, C18orf49,MPZL3, UTS2, FAM70B, UTS2, LOC254128, LGR6, IL8, CHML, STX7, PROCR,VAPA, LAG3, OASL, LOC100132181, HLA-DRB4, CCL2, UGCG, PDXDC1, andALS2CR11.

In some embodiments, the solid support comprises a plurality of nucleicacids that hybridize to a plurality of lacunar stroke-associated genesselected from the group consisting of HLA-DQA1, FLJ13773, RASEF, CALM1,QKI, TTC12, CCL3///CCL3L1///CCL3L3, CCDC78, PRSS23, LAIR2, C18orf49,MPZL3, UTS2, FAM70B, UTS2, LOC254128, LGR6, IL8, CHML, and STX7.

In some embodiments, the solid support comprises a plurality of nucleicacids that hybridize to a plurality of lacunar stroke-associated genesselected from the group consisting of HLA-DQA1, FLJ13773, RASEF, CALM1,QKI, TTC12, CCL3///CCL3L1///CCL3L3, CCDC78, PRSS23, and LAIR2.

In various embodiments, the solid support further comprises a pluralityof nucleic acids that hybridize to a plurality of endogenous referencegenes selected from the group consisting of USP7, MAPRE2, CSNK1G2,SAFB2, PRKAR2A, PI4 KB, CRTC1, HADHA, MAP1LC3B, KAT5, CDC2L1///CDC2L2,GTSE1, TCF25, CHP, LRRC40, hCG_2003956///LYPLA2///LYPLA2P1, DAXX,UBE2NL, EIF1, KCMF1, PRKRIP1, CHMP4A, TMEM184C, TINF2, PODNL1, FBXO42,LOC441258, RRP1, C10orf104, ZDHHC5, C9orf23, LRRC45, NACC1,LOC100133445///LOC115110, PEX16.

In various embodiments, the solid support further comprises a pluralityof nucleic acids that hybridize to a plurality of ischemicstroke-associated biomarkers selected from the group consisting of FAT3,GADL1, CXADR, RNF141, CLEC4E, TIMP2, ANKRD28, TIMM8A, PTPRD, CCRL1,FCRL4, DLX6, GABRB2, GYPA, PHTF1, CKLF, CKLF, RRAGD, CLEC4E, CKLF, FGD4,CPEB2, LOC100290882, UBXN2B, ENTPD1, BST1, LTB4R, F5, IFRD1, KIAA0319,CHMP1B, MCTP1, VNN3, AMN1, LAMP2, FCHO2, ZNF608, REM2, QKI, RBM25, FAR2,ST3GAL6, HNRNPH2, GAB1, UBR5, VAPA, MCTP1, SH3GL3, PGM5,CCDC144C///LOC100134159, LECT2, SHOX, TBX5, SPTLC3, SNIP, RBMS3, P704P,THSD4, SNRPN, GLYATL1, DKRZP434L187, OVOL2, SPIB, BXDC5, UNC5B, ASTN2,FLJ35934, CCDC144A, ALDOAP2, LDB3, LOC729222///PPFIBP1, HNRNPUL2,ELAVL2, PRTG, FOXA2, SCD5, LOC283027, LOC344595, RPL22, LOC100129488 andRPL22.

In various embodiments, the solid support further comprises a pluralityof nucleic acids that hybridize to a plurality of cardioembolicstroke-associated biomarkers selected from the group consisting of IRF6,ZNF254, GRM5, EXT2, AP3S2, PIK3C2B, ARHGEF5, COL13A1, PTPN20A///PTPN20B,LHFP, BANK1, HLA-DOA, EBF1, TMEM19, LHFP, FCRL1, OOEP, LRRC37A3,LOC284751, CD46, ENPP2, C19orf28, TSKS, CHURC1, ADAMTSL4, FLJ40125,CLEC18A, ARHGEF12, C16orf68, TFDP1 and GSTK1.

In various embodiments, the solid support further comprises a pluralityof nucleic acids that hybridize to a plurality of carotidstenosis-associated biomarkers selected from the group consisting ofNT5E, CLASP2, GRM5, PROCR, ARHGEF5, AKR1C3, COL13A1, LHFP, RNF7, CYTH3,EBF1, RANBP10, PRSS35, C12orf42, LOC100127980, FLJ31945, LOC284751,LOC100271832, MTBP, ICAM4, SHOX2, DOPEY2, CMBL, LOC146880, SLC20A1,SLC6A19, ARHGEF12, C16orf68, GIPC2 and LOC100144603.

In various embodiments, the solid support further comprises a pluralityof nucleic acids that hybridize to a plurality of atrialfibrillation-associated biomarkers selected from the group consisting ofSMC1A, SNORA68, GRLF1, SDC4, HIPK2, LOC100129034, CMTM1, TTC7A, LRRC43,MIF///SLC2A11, PER3, PPIE, COL13A1, DUSP16, LOC100129034, BRUNOL6,GPR176, C6orf164 and MAP3K7IP1.

In various embodiments, the solid support further comprises a pluralityof nucleic acids that hybridize to a plurality of transient ischemicattack-associated biomarkers selected from the group consisting ofGABRB2, ELAVL3, COL1A1, SHOX2, GABRB2, TWIST1, DPPA4, DKFZP434P211,WIT1, SOX9, DLX6, ANXA3, EPHA3, SOX11, SLC26A8, CCRL1, FREM2, STOX2,ZNF479, LOC338862, ASTN2, FOLH1, SNX31, KREMEN1, ZNF479, ALS2CR11, FIGN,RORB, LOC732096, GYPA, ALPL, LHX2, GALNT5, SRD5A2L2, GALNT14, OVOL2,BMPR1B, UNC5B, ODZ2, ALPL, RASAL2, SHOX, C19orf59, ZNF114, SRGAP1,ELAVL2, NCRNA00032, LOC440345, FLJ30375, TFPI, PTGR1, ROBO1, NR2F2,GRM5, LUM, FLJ39051, COL1A2, CASP5, OPCML, TTC6, TFAP2B, CRISP2, SOX11,ANKRD30B, FLJ39051, SCN2A, MYNN, FOXA2, DKFZP434B061, LOC645323, SNIP,LOC645323, LOC374491, ADAM30, SIX3, FLJ36144, CARD8, KREMEN1,RP1-127L4.6, FAM149A, B3GAT2, SPOCK3, G30, ITGBL1, IQGAP3, C7orf45,ZNF608, LOC375010, LRP2, TGFB2, SHOX2, HOXC4///HOXC6, ELTD1,FAM182B///RP13-401N8.2, PRO0478, LIFR, FOLH1, EHF, NDST3, BRUNOL5,LOC728460, PDE1A, POU2AF1, FAT1, PCDH11X///PCDH11Y, FLJ37786, SLC22A4,DHRS13, EHF, MEG3, PIWIL1, LOC203274, LOC100133920///LOC286297, DMRT1,ADM, VWA3B, GAFA3, HESX1, ADAMDEC1, CAV1, LAMB4, TPTE, PPP1R1C, HPSE,AIM2, RUNDC3B, CARD16, FAM124A, MGC39584, OSM, RFX2, MYBPC1, LTBR,C18orf2, SNRPN, FLJ36031, IL1B, TRPM1, OSTCL, MAPK14,KCNJ15///LOC100131955, FIGN, HNT, S100A12, CHIT1, C7orf53, FAM13A1,GNAO1, MAPK14, FAM55D, PRKD2, LIMK2, C18orf54, IGFBP5, EVI1, PLSCR1,FOXC1, LOC646627, ZNF462, CNTLN, ZNF438, DEFB105A///DEFB105B, LOC340017,C1orf67, ACSL1, ADH1B, SLC2A14///SLC2A3, IL1B, ST3GAL4, UBE2J1, PNPLA3,PAPPA, NBPF10///RP11-94I2.2, SFXN1, SPIN3, UNC84A, OLFM2, PPM1K, P2RY10,ZNF512B, MORF4L2, GIGYF2, ERAP2, SLFN13, LOC401431, MED6,BAIAP2L1///LOC100128461, LNPEP, MBNL1, NOS3, MCF2L, KIAA1659, SCAMP5,LOC648921, ANAPC5, SPON1, FUS, GPR22, GAL3ST4, METTL3, LOC100131096,FAAH2, SMURF2, SNRPN, FBLN7, GLS, G3BP1, RCAN3, EPHX2, DIP2C, CCDC141,CLTC, FOSB, CACNA1I, UNQ6228, ATG9B, AK5, SPIN3, RBM14, SNRPN, MAN1C1,HELLS, EDAR, SLC3A1, ZNF519,LOC100130070///LOC100130775///LOC100131787///LOC100131905///LOC100132291///LOC100132488///RPS27,ZC3H12B, IQGAP2, SOX8, WHDC1L2, TNPO1, TNFRSF21, TSHZ2,DMRTC1///DMRTC1B, GSTM1, GSTM2, PNMA6A, CAND1, CCND3, GSTM1, and GUSBL2.

In some embodiments, the solid support is a microarray. In variousembodiments, the microarray has 1000 or fewer hybridizing nucleic acids,for example, 900, 800, 700, 600, 500 or fewer hybridizing nucleic acids.In various embodiments, the microarray does not comprise nucleic acidsthat hybridize to genes whose expression is not correlative of orassociated with ischemia.

DEFINITIONS

Unless defined otherwise, all technical and scientific terms used hereingenerally have the same meaning as commonly understood by one ofordinary skill in the art to which this invention belongs. Generally,the nomenclature used herein and the laboratory procedures in cellculture, molecular genetics, organic chemistry and nucleic acidchemistry and hybridization described below are those well-known andcommonly employed in the art. Standard techniques are used for nucleicacid and peptide synthesis. Generally, enzymatic reactions andpurification steps are performed according to the manufacturer'sspecifications. The techniques and procedures are generally performedaccording to conventional methods in the art and various generalreferences (see generally, Sambrook et al. MOLECULAR CLONING: ALABORATORY MANUAL, 3rd ed. (2001) Cold Spring Harbor Laboratory Press,Cold Spring Harbor, N.Y. and Ausubel, et al., CURRENT PROTOCOLS INMOLECULAR BIOLOGY, 1990-2008, Wiley Interscience), which are providedthroughout this document. The nomenclature used herein and thelaboratory procedures in analytical chemistry, and organic syntheticdescribed below are those well-known and commonly employed in the art.Standard techniques, or modifications thereof, are used for chemicalsyntheses and chemical analyses.

“Ischemia” or “ischemic event” as used herein refers to diseases anddisorders characterized by inadequate blood supply (i.e., circulation)to a local area due to blockage of the blood vessels to the area.Ischemia includes for example, strokes and transient ischemic attacks.Strokes include, e.g., ischemic stroke (including, but not limited to,cardioembolic strokes, atheroembolic or atherothrombotic strokes, i.e.,strokes caused by atherosclerosis in the carotid, aorta, heart, andbrain, small vessel strokes (i.e., lacunar strokes), strokes caused bydiseases of the vessel wall, i.e., vasculitis, strokes caused byinfection, strokes caused by hematological disorders, strokes caused bymigraines, and strokes caused by medications such as hormone therapy),hemorrhagic ischemic stroke, intracerebral hemorrhage, and subarachnoidhemorrhage.

The term “small deep infarct” or “small deep infarction” or “SDI”interchangeably refer to focal infarction of the brain due to anuncertain cause, including but not limited to, cardioembolic,atheroembolic, atherosclerotic disease of the parent artery or diseaseof the perforating artery.

The term “lacunar stroke” or “lacune” interchangeably refer to focalinfarction of the brain due to perforating branch occlusion frommicroatheroma or lipohyalinosis. Implicit in this definition of lacunarstroke is that the: 1) infarction is not due to cardioembolic source; 2)infarction is not due to atherosclerotic disease of parent arteries; 3)infarction occurs in regions of the brain supplied by penetratingarteries, e.g., basal ganglia, thalamus, internal capsule, coronaradiata or pons; 4) lacunar stroke is oftentimes associated with thepresence of hypertension, diabetes or other vascular risk factors; and5) infarcts tend to be smaller, generally less than 50 mm in diameter.When the cause of stroke is uncertain or likely other than perforatingartery disease, then the more general term—small deep infarct—isappropriate. See, e.g., Caplan, Stroke (2003) 34(3):653-9; Norrving,Pract Neurol (2008) 8:222-228; Lastilla, Clin Exp Hypertens. (2006)28(3-4):205-15; and Arboix and Marti-Vilalta, Expert Rev Neurother.(2009) 9(2):179-96.

The term “transient ischemic attack,” “TIA,” or “mini-stroke”interchangeably refer to a change in the blood supply to a particulararea of the brain, resulting in brief neurologic dysfunction thatpersists, by definition, for less than 24 hours. By definition, a TIAresolves within 24 hours, but most TIA symptoms resolve within 1 hour.If symptoms persist longer, then it is categorized as a stroke. Symptomsinclude temporary loss of vision (typically amaurosis fugax); difficultyspeaking (aphasia); weakness on one side of the body (hemiparesis);numbness or tingling (paresthesia), usually on one side of the body, anddizziness, lack of coordination or poor balance. The symptoms of a TIAusually last a few minutes and with resolution of most symptoms within60 minutes.

“Reference expression profile” refers to the pattern of expression of aset of genes (e.g., a plurality of the genes set forth in Tables 3 and4) differentially expressed (i.e., overexpressed or underexpressed) inischemia relative to a control (e.g., the expression level in anindividual free of an ischemic event or the expression level of a stablyexpressed endogenous reference biomarker). A gene from Tables 3 and 4that is expressed at a level that is at least about 1.2-, 1.3-, 1.4-,1.5-, 1.6-, 1.7-, 1.8-, 1.9-, 2.0-, 2.1-, 2.2-, 2.3-, 2.4-, 2.5-,2.6-,2.7-, 2.8-, 2.9-, 3.0-, 3.1-, 3.2-, 3.3-, 3.4- or 3.5-fold higher thanthe level in a control is a gene overexpressed in ischemia and a genefrom Tables 3 and 4 that is expressed at a level that is at least about1.2-, 1.3-, 1.4-, 1.5-, 1.6-, 1.7-, 1.8-, 1.9-, 2.0-, 2.1-, 2.2-, 2.3-,2.4-, 2.5-, 2.6-, 2.7-, 2.8-, 2.9-, 3.0-, 3.1-, 3.2-, 3.3-, 3.4- or3.5-fold lower than the level in a control is a gene underexpressed inischemia. Alternately, genes that are expressed at a level that is atleast about 10%, 20%, 30%, 40%, 50%, 60%, 70%, 80%, 90%, or 100% higherthan the level in a control is a gene overexpressed in ischemia and agene that is expressed at a level that is at least about 10%, 20%, 30%,40%, 50%, 60%, 70%, 80%, 90%, or 100% lower than the level in a controlis a gene underexpressed in ischemia.

A “plurality” refers to two or more, for example, 2, 3, 4, 5, 6, 7, 8,9, 10, 11, 12, 13, 14, 15, 16, 17, 18, 19, 20, 21, 22, 23 or more (e.g.,genes). In some embodiments, a plurality refers to concurrent orsequential determination of about 15-85, 20-60 or 40-50 genes, forexample, about 15, 20, 25, 30, 35, 40, 45, 50, 55, 60, 65, 70, 75, 80,85, 90, 95 or 100, or more, genes. In some embodiments, “plurality”refers to all genes listed in one or more tables, e.g., all genes listedin Tables 3 and 4.

“Sample” or “biological sample” includes sections of tissues such asbiopsy and autopsy samples, and frozen sections taken for histologicpurposes. Such samples include blood, sputum, tissue, lysed cells, brainbiopsy, cultured cells, e.g., primary cultures, explants, andtransformed cells, stool, urine, etc. A biological sample is typicallyobtained from a eukaryotic organism, most preferably a mammal such as aprimate, e.g., chimpanzee or human; cow; dog; cat; a rodent, e.g.,guinea pig, rat, mouse; rabbit; or a bird; reptile; or fish.

“Array” as used herein refers to a solid support comprising attachednucleic acid or peptide probes. Arrays typically comprise a plurality ofdifferent nucleic acid or peptide probes that are coupled to a surfaceof a substrate in different, known locations. These arrays, alsodescribed as “microarrays” or colloquially “chips” have been generallydescribed in the art, for example, U.S. Pat. Nos. 5,143,854, 5,445,934,5,744,305, 5,677,195, 6,040,193, 5,424,186 and Fodor et al., Science,251:767-777 (1991). These arrays may generally be produced usingmechanical synthesis methods or light directed synthesis methods whichincorporate a combination of photolithographic methods and solid phasesynthesis methods. Techniques for the synthesis of these arrays usingmechanical synthesis methods are described in, e.g., U.S. Pat. No.5,384,261. Arrays may comprise a planar surface or may be nucleic acidsor peptides on beads, gels, polymeric surfaces, fibers such as fiberoptics, glass or any other appropriate substrate as described in, e.g.,U.S. Pat. Nos. 5,770,358, 5,789,162, 5,708,153, 6,040,193 and 5,800,992.Arrays may be packaged in such a manner as to allow for diagnostics orother manipulation of an all-inclusive device, as described in, e.g.,U.S. Pat. Nos. 5,856,174 and 5,922,591.

The term “gene” means the segment of DNA involved in producing apolypeptide chain; it includes regions preceding and following thecoding region (leader and trailer) as well as intervening sequences(introns) between individual coding segments (exons).

The terms “nucleic acid” and “polynucleotide” are used interchangeablyherein to refer to deoxyribonucleotides or ribonucleotides and polymersthereof in either single- or double-stranded form. The term encompassesnucleic acids containing known nucleotide analogs or modified backboneresidues or linkages, which are synthetic, naturally occurring, andnon-naturally occurring, which have similar binding properties as thereference nucleic acid, and which are metabolized in a manner similar tothe reference nucleotides. Examples of such analogs include, withoutlimitation, phosphorothioates, phosphoramidates, methyl phosphonates,chiral-methyl phosphonates, 2-O-methyl ribonucleotides, peptide-nucleicacids (PNAs).

Unless otherwise indicated, a particular nucleic acid sequence alsoencompasses conservatively modified variants thereof (e.g., degeneratecodon substitutions) and complementary sequences, as well as thesequence explicitly indicated. Specifically, degenerate codonsubstitutions may be achieved by generating sequences in which the thirdposition of one or more selected (or all) codons is substituted withmixed-base and/or deoxyinosine residues (Batzer et al., Nucleic AcidRes. 19:5081 (1991); Ohtsuka et al., J. Biol. Chem. 260:2605-2608(1985); Rossolini et al., Mol. Cell. Probes 8:91-98 (1994)). The termnucleic acid is used interchangeably with gene, cDNA, mRNA,oligonucleotide, and polynucleotide.

The phrase “stringent hybridization conditions” refers to conditionsunder which a probe will hybridize to its target subsequence, typicallyin a complex mixture of nucleic acid, but to no other sequences.Stringent hybridization conditions are sequence-dependent and will bedifferent in different circumstances. Longer sequences hybridizespecifically at higher temperatures. An extensive guide to thehybridization of nucleic acids is found in Tijssen, Techniques inBiochemistry and Molecular Biology—Hybridization with Nucleic Probes,“Overview of principles of hybridization and the strategy of nucleicacid assays” (1993). Generally, stringent hybridization conditions areselected to be about 5-10° C. lower than the thermal melting point forthe specific sequence at a defined ionic strength Ph. The T_(m) is thetemperature (under defined ionic strength, Ph, and nucleicconcentration) at which 50% of the probes complementary to the targethybridize to the target sequence at equilibrium (as the target sequencesare present in excess, at T_(m), 50% of the probes are occupied atequilibrium). Stringent hybridization conditions will be those in whichthe salt concentration is less than about 1.0 M sodium ion, typicallyabout 0.01 to 1.0 M sodium ion concentration (or other salts) at Ph 7.0to 8.3 and the temperature is at least about 30° C. for short probes(e.g., 10 to 50 nucleotides) and at least about 60° C. for long probes(e.g., greater than 50 nucleotides). Stringent hybridization conditionsmay also be achieved with the addition of destabilizing agents such asformamide. For selective or specific hybridization, a positive signal isat least two times background, optionally 10 times backgroundhybridization. Exemplary stringent hybridization conditions can be asfollowing: 50% formamide, 5×SSC, and 1% SDS, incubating at 42° C., or,5×SSC, 1% SDS, incubating at 65° C., with wash in 0.2×SSC, and 0.1% SDSat 65° C.

Nucleic acids that do not hybridize to each other under stringenthybridization conditions are still substantially identical if thepolypeptides which they encode are substantially identical. This occurs,for example, when a copy of a nucleic acid is created using the maximumcodon degeneracy permitted by the genetic code. In such cases, thenucleic acids typically hybridize under moderately stringenthybridization conditions. Exemplary “moderately stringent hybridizationconditions” include a hybridization in a buffer of 40% formamide, 1 MNaCl, 1% SDS at 37° C., and a wash in 1×SSC at 45° C. A positivehybridization is at least twice background. Those of ordinary skill willreadily recognize that alternative hybridization and wash conditions canbe utilized to provide conditions of similar stringency.

The terms “isolated,” “purified,” or “biologically pure” refer tomaterial that is substantially or essentially free from components thatnormally accompany it as found in its native state. Purity andhomogeneity are typically determined using analytical chemistrytechniques such as polyacrylamide gel electrophoresis or highperformance liquid chromatography. A protein that is the predominantspecies present in a preparation is substantially purified. The term“purified” denotes that a nucleic acid or protein gives rise toessentially one band in an electrophoretic gel. Particularly, it meansthat the nucleic acid or protein is at least 85% pure, more preferablyat least 95% pure, and most preferably at least 99% pure.

The term “heterologous” when used with reference to portions of anucleic acid indicates that the nucleic acid comprises two or moresubsequences that are not found in the same relationship to each otherin nature. For instance, the nucleic acid is typically recombinantlyproduced, having two or more sequences from unrelated genes arranged tomake a new functional nucleic acid, e.g., a promoter from one source anda coding region from another source. Similarly, a heterologous proteinindicates that the protein comprises two or more subsequences that arenot found in the same relationship to each other in nature (e.g., afusion protein).

An “expression vector” is a nucleic acid construct, generatedrecombinantly or synthetically, with a series of specified nucleic acidelements that permit transcription of a particular nucleic acid in ahost cell. The expression vector can be part of a plasmid, virus, ornucleic acid fragment. Typically, the expression vector includes anucleic acid to be transcribed operably linked to a promoter.

The terms “polypeptide,” “peptide” and “protein” are usedinterchangeably herein to refer to a polymer of amino acid residues. Theterms apply to amino acid polymers in which one or more amino acidresidue is an artificial chemical mimetic of a corresponding naturallyoccurring amino acid, as well as to naturally occurring amino acidpolymers and non-naturally occurring amino acid polymer.

The term “amino acid” refers to naturally occurring and synthetic aminoacids, as well as amino acid analogs and amino acid mimetics thatfunction in a manner similar to the naturally occurring amino acids.Naturally occurring amino acids are those encoded by the genetic code,as well as those amino acids that are later modified, e.g.,hydroxyproline, α-carboxyglutamate, and O-phosphoserine. “Amino acidanalogs” refers to compounds that have the same basic chemical structureas a naturally occurring amino acid, i.e., an a carbon that is bound toa hydrogen, a carboxyl group, an amino group, and an R group, e.g.,homoserine, norleucine, methionine sulfoxide, methionine methylsulfonium. Such analogs have modified R groups (e.g., norleucine) ormodified peptide backbones, but retain the same basic chemical structureas a naturally occurring amino acid. “Amino acid mimetics” refers tochemical compounds that have a structure that is different from thegeneral chemical structure of an amino acid, but that functions in amanner similar to a naturally occurring amino acid.

Amino acids may be referred to herein by either their commonly knownthree letter symbols or by the one-letter symbols recommended by theIUPAC-IUB Biochemical Nomenclature Commission. Nucleotides, likewise,may be referred to by their commonly accepted single-letter codes.

“Conservatively modified variants” applies to both amino acid andnucleic acid sequences. With respect to particular nucleic acidsequences, conservatively modified variants refers to those nucleicacids which encode identical or essentially identical amino acidsequences, or where the nucleic acid does not encode an amino acidsequence, to essentially identical sequences. Because of the degeneracyof the genetic code, a large number of functionally identical nucleicacids encode any given protein. For instance, the codons GCA, GCC, GCGand GCU all encode the amino acid alanine. Thus, at every position wherean alanine is specified by a codon, the codon can be altered to any ofthe corresponding codons described without altering the encodedpolypeptide. Such nucleic acid variations are “silent variations,” whichare one species of conservatively modified variations. Every nucleicacid sequence herein which encodes a polypeptide also describes everypossible silent variation of the nucleic acid. One of skill willrecognize that each codon in a nucleic acid (except AUG, which isordinarily the only codon for methionine, and TGG, which is ordinarilythe only codon for tryptophan) can be modified to yield a functionallyidentical molecule. Accordingly, each silent variation of a nucleic acidwhich encodes a polypeptide is implicit in each described sequence.

As to amino acid sequences, one of skill will recognize that individualsubstitutions, deletions or additions to a nucleic acid, peptide,polypeptide, or protein sequence which alters, adds or deletes a singleamino acid or a small percentage of amino acids in the encoded sequenceis a “conservatively modified variant” where the alteration results inthe substitution of an amino acid with a chemically similar amino acid.Conservative substitution tables providing functionally similar aminoacids are well known in the art. Such conservatively modified variantsare in addition to and do not exclude polymorphic variants, interspecieshomologs, and alleles of the invention.

The following eight groups each contain amino acids that areconservative substitutions for one another:

-   1) Alanine (A), Glycine (G);-   2) Aspartic acid (D), Glutamic acid (E);-   3) Asparagine (N), Glutamine (Q);-   4) Arginine I, Lysine (K);-   5) Isoleucine (I), Leucine (L), Methionine (M), Valine (V);-   6) Phenylalanine (F), Tyrosine (Y), Tryptophan (W);-   7) Serine (S), Threonine (T); and-   8) Cysteine (C), Methionine (M)-   (see, e.g., Creighton, Proteins (1984)).

The terms “identical” or percent “identity,” in the context of two ormore nucleic acids or polypeptide sequences, refer to two or moresequences or subsequences that are the same or have a specifiedpercentage of amino acid residues or nucleotides that are the same(i.e., 60% identity, preferably 65%, 70%, 75%, 80%, 85%, 90%, or 95%identity over a specified region of an ischemia-associated gene (e.g., agene set forth in Tables 3 and 4), when compared and aligned for maximumcorrespondence over a comparison window, or designated region asmeasured using one of the following sequence comparison algorithms or bymanual alignment and visual inspection. Such sequences are then said tobe “substantially identical.” This definition also refers to thecompliment of a test sequence. Preferably, the identity exists over aregion that is at least about 25 amino acids or nucleotides in length,or more preferably over a region that is 50-100 amino acids ornucleotides in length, or over the full length of the sequence.

For sequence comparison, typically one sequence acts as a referencesequence, to which test sequences are compared. When using a sequencecomparison algorithm, test and reference sequences are entered into acomputer, subsequence coordinates are designated, if necessary, andsequence algorithm program parameters are designated. Default programparameters can be used, or alternative parameters can be designated. Thesequence comparison algorithm then calculates the percent sequenceidentities for the test sequences relative to the reference sequence,based on the program parameters. For sequence comparison of nucleicacids and proteins to ischemia-associated nucleic acids and proteins,the BLAST and BLAST 2.0 algorithms and the default parameters discussedbelow are used.

A “comparison window”, as used herein, includes reference to a segmentof any one of the number of contiguous positions selected from the groupconsisting of from 20 to 600, usually about 50 to about 200, moreusually about 100 to about 150 in which a sequence may be compared to areference sequence of the same number of contiguous positions after thetwo sequences are optimally aligned. Methods of alignment of sequencesfor comparison are well-known in the art. Optimal alignment of sequencesfor comparison can be conducted, e.g., by the local homology algorithmof Smith & Waterman, Adv. Appl. Math. 2:482 (1981), by the homologyalignment algorithm of Needleman & Wunsch, J. Mol. Biol. 48:443 (1970),by the search for similarity method of Pearson & Lipman, Proc. Nat'l.Acad. Sci. USA 85:2444 (1988), by computerized implementations of thesealgorithms (GAP, BESTFIT, FASTA, and TFASTA in the Wisconsin GeneticsSoftware Package, Genetics Computer Group, 575 Science Dr., Madison,Wis.), or by manual alignment and visual inspection (see, e.g., CurrentProtocols in Molecular Biology (Ausubel et al., eds. 1995 supplement)).

A preferred example of algorithm that is suitable for determiningpercent sequence identity and sequence similarity are the BLAST andBLAST 2.0 algorithms, which are described in Altschul et al., Nuc. AcidsRes. 25:3389-3402 (1977) and Altschul et al., J. Mol. Biol. 215:403-410(1990), respectively. BLAST and BLAST 2.0 are used, with the parametersdescribed herein, to determine percent sequence identity for the nucleicacids and proteins of the invention. Software for performing BLASTanalyses is publicly available through the National Center forBiotechnology Information (on the internet at ncbi.nlm.nih.gov/). Thisalgorithm involves first identifying high scoring sequence pairs (HSPs)by identifying short words of length W in the query sequence, whicheither match or satisfy some positive-valued threshold score T whenaligned with a word of the same length in a database sequence. T isreferred to as the neighborhood word score threshold (Altschul et al.,supra). These initial neighborhood word hits act as seeds for initiatingsearches to find longer HSPs containing them. The word hits are extendedin both directions along each sequence for as far as the cumulativealignment score can be increased. Cumulative scores are calculatedusing, for nucleotide sequences, the parameters M (reward score for apair of matching residues; always >0) and N (penalty score formismatching residues; always <0). For amino acid sequences, a scoringmatrix is used to calculate the cumulative score. Extension of the wordhits in each direction are halted when: the cumulative alignment scorefalls off by the quantity X from its maximum achieved value; thecumulative score goes to zero or below, due to the accumulation of oneor more negative-scoring residue alignments; or the end of eithersequence is reached. The BLAST algorithm parameters W, T, and Xdetermine the sensitivity and speed of the alignment. The BLASTN program(for nucleotide sequences) uses as defaults a word length (W) of 11, anexpectation (E) of 10, M=5, N=−4 and a comparison of both strands. Foramino acid sequences, the BLASTP program uses as defaults a word lengthof 3, and expectation (E) of 10, and the BLOSUM62 scoring matrix (seeHenikoff & Henikoff, Proc. Natl. Acad. Sci. USA 89:10915 (1989))alignments (B) of 50, expectation (E) of 10, M=5, N=−4, and a comparisonof both strands.

The BLAST algorithm also performs a statistical analysis of thesimilarity between two sequences (see, e.g., Karlin & Altschul, Proc.Nat'l. Acad. Sci. USA 90:5873-5787 (1993)). One measure of similarityprovided by the BLAST algorithm is the smallest sum probability (P(N)),which provides an indication of the probability by which a match betweentwo nucleotide or amino acid sequences would occur by chance. Forexample, a nucleic acid is considered similar to a reference sequence ifthe smallest sum probability in a comparison of the test nucleic acid tothe reference nucleic acid is less than about 0.2, more preferably lessthan about 0.01, and most preferably less than about 0.001.

An indication that two nucleic acid sequences or polypeptides aresubstantially identical is that the polypeptide encoded by the firstnucleic acid is immunologically cross reactive with the antibodiesraised against the polypeptide encoded by the second nucleic acid, asdescribed below. Thus, a polypeptide is typically substantiallyidentical to a second polypeptide, for example, where the two peptidesdiffer only by conservative substitutions. Another indication that twonucleic acid sequences are substantially identical is that the twomolecules or their complements hybridize to each other under stringentconditions, as described below. Yet another indication that two nucleicacid sequences are substantially identical is that the same primers canbe used to amplify the sequence.

The phrase “selectively (or specifically) hybridizes to” refers to thebinding, duplexing, or hybridizing of a molecule only to a particularnucleotide sequence under stringent hybridization conditions when thatsequence is present in a complex mixture (e.g., total cellular orlibrary DNA or RNA).

By “host cell” is meant a cell that contains an expression vector andsupports the replication or expression of the expression vector. Hostcells may be, for example, prokaryotic cells such as E. coli oreukaryotic cells such as yeast cells or mammalian cells such as CHOcells.

“Inhibitors,” “activators,” and “modulators” of expression or ofactivity are used to refer to inhibitory, activating, or modulatingmolecules, respectively, identified using in vitro and in vivo assaysfor expression or activity, e.g., ligands, agonists, antagonists, andtheir homologs and mimetics. The term “modulator” includes inhibitorsand activators. Inhibitors are agents that, e.g., inhibit expression ofa polypeptide or polynucleotide of the invention or bind to, partiallyor totally block stimulation or enzymatic activity, decrease, prevent,delay activation, inactivate, desensitize, or down regulate the activityof a polypeptide or polynucleotide of the invention, e.g., antagonists.Activators are agents that, e.g., induce or activate the expression of apolypeptide or polynucleotide of the invention or bind to, stimulate,increase, open, activate, facilitate, enhance activation or enzymaticactivity, sensitize or up regulate the activity of a polypeptide orpolynucleotide of the invention, e.g., agonists. Modulators includenaturally occurring and synthetic ligands, antagonists, agonists, smallchemical molecules and the like. Assays to identify inhibitors andactivators include, e.g., applying putative modulator compounds tocells, in the presence or absence of a polypeptide or polynucleotide ofthe invention and then determining the functional effects on apolypeptide or polynucleotide of the invention activity. Samples orassays comprising a polypeptide or polynucleotide of the invention thatare treated with a potential activator, inhibitor, or modulator arecompared to control samples without the inhibitor, activator, ormodulator to examine the extent of effect. Control samples (untreatedwith modulators) are assigned a relative activity value of 100%.Inhibition is achieved when the activity value of a polypeptide orpolynucleotide of the invention relative to the control is about 80%,optionally 50% or 25-1%. Activation is achieved when the activity valueof a polypeptide or polynucleotide of the invention relative to thecontrol is 110%, optionally 150%, optionally 200-500%, or 1000-3000%higher.

The term “test compound” or “drug candidate” or “modulator” orgrammatical equivalents as used herein describes any molecule, eithernaturally occurring or synthetic, e.g., protein, oligopeptide (e.g.,from about 5 to about 25 amino acids in length, preferably from about 10to 20 or 12 to 18 amino acids in length, preferably 12, 15, or 18 aminoacids in length), small organic molecule, polysaccharide, lipid, fattyacid, polynucleotide, RNAi, oligonucleotide, etc. The test compound canbe in the form of a library of test compounds, such as a combinatorialor randomized library that provides a sufficient range of diversity.Test compounds are optionally linked to a fusion partner, e.g.,targeting compounds, rescue compounds, dimerization compounds,stabilizing compounds, addressable compounds, and other functionalmoieties. Conventionally, new chemical entities with useful propertiesare generated by identifying a test compound (called a “lead compound”)with some desirable property or activity, e.g., inhibiting activity,creating variants of the lead compound, and evaluating the property andactivity of those variant compounds. Often, high throughput screening(HTS) methods are employed for such an analysis.

A “small organic molecule” refers to an organic molecule, eithernaturally occurring or synthetic, that has a molecular weight of morethan about 50 Daltons and less than about 2500 Daltons, preferably lessthan about 2000 Daltons, preferably between about 100 to about 1000Daltons, more preferably between about 200 to about 500 Daltons.

BRIEF DESCRIPTION OF THE DRAWINGS

FIGS. 1A and 1B illustrate how gene expression analysis can be used todistinguish lacunar from non-lacunar stroke. 1A provides an illustrativecluster plot of 41 probesets corresponding to 40 genes that discriminatelacunar from non-lacunar stroke. Genes are shown on the y-axis andstrokes of lacunar, and non-lacunar (arterial and cardioembolic)etiologies are shown on the x-axis. Up regulated genes are shown in red,and down regulated genes in blue. 1B illustrates the fold change of the41 probesets. There is a group of genes that are down-regulated inlacunar stroke and up regulated in non-lacunar stroke. Similarly, thereis a group of genes that are up-regulated in lacunar stroke and downregulated in non-lacunar stroke. These genes can be used to discriminatelacunar from non-lacunar stroke.

FIG. 2 illustrates box and whisker plots of the gene expression valuesfor the 41 probesets that distinguished lacunar stroke from non-lacunarstroke. Lacunar stroke is shown in orange (upper plot), and non-lacunarstroke in green (lower plot). Each probeset demonstrates significantdifference in gene expression between groups. However, no singleprobeset is able to completely separate every single patient withlacunar stroke from every patient with non-lacunar stroke. By combininginformation from multiple genes in the profile, the separation oflacunar from non-lacunar stroke is achieved for nearly all patientsstudied.

FIG. 3 illustrates a receiver operating characteristics (ROC) curve ofthe 41 probesets (40 genes) showing the sensitivity and specificity atvarious instance probabilities for the prediction of lacunar versusnon-lacunar stroke.

FIGS. 4A and 4B illustrate a probability plot of the predicted diagnosisof lacunar and non-lacunar stroke based on 10-fold cross-validationanalysis using the linear discriminant analysis model for the 41probesets (40 genes). 4A illustrates the predicted probability oflacunar and non-lacunar stroke in the 30 patients diagnosed clinicallyas lacunar stroke. Eight subjects were predicted to have a geneexpression profile similar to those of non-lacunar stroke, and 22 werepredicted to be lacunar stroke. 4B illustrates the predicted probabilityof non-lacunar and lacunar stroke in the 86 patients with non-lacunarstroke. Eighty of the 86 were correctly predicted to be non-lacunarstroke.

DETAILED DESCRIPTION

1. Introduction

Small deep infarcts including lacunar stroke account for greater thanone quarter of all ischemic strokes and are associated with increasedrisk of cardiovascular disease and dementia. Though lipohyalinosis ofsmall penetrating arteries (lacunar stroke) is the most common cause,emboli of arterial or cardiac origin are also causes. Determining whichsmall deep infarcts are caused by lacunar disease, arterial emboli, orcardiac emboli is challenging, but nevertheless important to deliveroptimal stroke prevention therapy.

184 ischemic strokes were analyzed to determine gene expression profilesuseful to distinguish lacunar from non-lacunar causes of small deepinfarcts. Lacunar stroke was defined as a lacunar syndrome associatedwith infarction<15 mm of the striatum, internal capsule, corona radiata,thalamus or pons. RNA was isolated from whole blood and processed onwhole genome microarrays. Differentially expressed genes between acutelacunar strokes (n=30) and non-lacunar strokes (n=86) were identified(false discovery rate≤0.05, fold change>|1.5|). A prediction model ableto discriminate lacunar from non-lacunar stroke was generated usinglinear discriminant analysis and evaluated using cross-validation and asecond test cohort of non-lacunar strokes (n=36). The model was thenapplied to predict etiology in small deep infarcts of unclear cause(size>15 mm or small deep infarct with potential embolic source) (n=32).A 41 gene profile discriminated lacunar from non-lacunar strokes withgreater than 90% sensitivity and specificity. Of the 32 small deepinfarcts of unclear cause, 17 were predicted to be of lacunar etiologyand 15 were predicted to be of non-lacunar etiology. Independentpredictors of lacunar stroke were non-Caucasian race/ethnicity andabsence of ipsilateral arterial disease. The identified profile largelyrepresents differences in immune response between stroke subtypesimportant to lacunar stroke. Accordingly, the present invention isbased, in part, on the discovery that gene expression profiles candistinguish lacunar from non-lacunar strokes. Small deep infarcts ofunclear cause were frequently predicted to be of non-lacunar etiology;subsequent work-up and analysis can be performed to identify potentialcardioembolic and/or arterial causes. Gene expression profiling may alsobe used to determine the clinical and treatment implications of smalldeep infarcts predicted to be of non-lacunar etiology.

Accordingly, the present invention is based, in part, on the discoverythat RNA expression profiling can be used to differentiate stroke oflacunar etiology from non-lacunar stroke. The invention provides a listof 41 probesets (corresponding to 40 genes) that have greater than 90%sensitivity and specificity to distinguish lacunar stroke fromnon-lacunar strokes. The genes identified herein to be associated withthe occurrence of and/or risk of experiencing lacunar stroke find use todiagnose lacunar stroke based upon an RNA expression profile. The use ofthe presently identified gene allow for the use of a blood test for therapid diagnosis of a lacunar cause of stroke.

In practice, the level of expression of genes associated with theoccurrence or risk of lacunar stroke can be measured in the blood ofpatients with an ischemic stroke. The expression of these genes can beassessed using any applicable method in the art, including, e.g.,RT-PCR, microarrays or other technology. In various embodiments, theexpression of these target genes can be normalized to internal controlgenes, which are known in the art. A panel of control genes that arespecific for ischemic stroke have been developed and are quite reliable.The endogenous control genes have fairly constant expression over manyage groups, different diseases, and both genders. Once the RNAexpression levels of the target genes (i.e., lacunar stroke-associatedgenes) are measured, and the RNA levels of the control genes aremeasured, then the target gene expression is normalized to the controlgenes. The expression levels of the normalized target genes can then beapplied to a linear discriminant analysis model to predict whether theblood sample is from a patient who has experience or is at risk ofexperiencing lacunar stroke and the probability that this is the case.Determining the expression levels of the presently identified lacunarstroke-associated genes, the sensitivity and specificity for predictionis greater than 90% for lacunar versus non-lacunar stroke.

A blood test for the diagnosis of stroke is useful in severalsituations. For example, the gene expression panel can be used topredict whether lacunar stroke is the cause of stroke in patients withsmall deep infarcts of the brain. About 25% of all stroke patients havesmall deep infarcts. These small deep infarcts can be caused by lacunarsmall vessel disease, but also by atherosclerotic disease or largerparent arteries and embolism form a cardiac source. An embolicatherosclerotic cause of stroke warrants a different investigativestrategy and treatment than a lacunar small vessel cause of stroke. Inparticular, it is important to diagnose disease that would guideappropriate disease treatment and management including the two mosteffective treatments for stroke: carotid surgery for symptomatic carotidstenosis and warfarin for symptomatic atrial fibrillation. Thus,ascertaining the etiology of small deep infarcts is of clinicalimportance.

Currently, patients presenting with a small deep infarct are mostlylabeled lacunar, and treated with anti-platelet agents. A diagnosisbased on the expression levels of the presently identified lacunarstroke-associated genes would identify the lacunar and non-lacunarstrokes, and thus guide appropriate treatment for stroke patients. Thepresently identified lacunar stroke-associated genes further find usefor diagnosing patients who have experienced or are at risk ofexperiencing Transient Ischemic Attacks. In these patients, the cause isoften unknown. Thus, a blood test predicting the cause of the TIA couldhelp prevent or ameliorate strokes in these patients.

The diagnosis of lacunar stroke presently requires a neurologist to takea history, perform an examination and then confirm using X-ray computedtomography (CT) or magnetic resonance imaging (MRI) brain scanning, inaddition to vascular imaging of the head and neck with doppler ormagnetic resonance angiography (MRA) or CT angiography (CTA); anelectrocardiogram (EKG or ECG), cardiac ultrasound and cardiacmonitoring; and a series of blood tests. Even with all theseinvestigations, some uncertainty in the diagnosis of lacunar strokeremains, as potential arterial and cardiac causes can be missed. Thepresent panel of lacunar stroke-associated genes provides a rapidblood-based test that can be performed at the point of care or in aclinical laboratory at low cost. Diagnosis of the presence or absence ofoccurrence or risk of lacunar stroke using the presently identifiedpanel of lacunar stroke-associated genes adds confidence to aphysicians' diagnosis of lacunar or non-lacunar stroke.

2. Patients Who can Benefit from the Present Methods

Individuals who will benefit from the present methods may be exhibitingsymptoms of ischemic stroke, and in particular, a small deep infarct(SDI). In some embodiments, the subject has experienced an ischemicevent. For example, the subject may have suffered or be currentlyexperiencing a small deep infarct, a transient ischemic attack (TIA), anischemic stroke, a myocardial infarction, peripheral vascular disease,or venous thromboembolism. The subject may have or have been diagnosedwith cerebral vascular disease.

Alternatively, the subject may be suspected of having experienced anischemic event, and in particular, a small deep infarct (SDI). Brainimaging on the patient may indicate microhemorrhage and/or blood-brainpermeability. In some embodiments, the levels of expression of the panelof biomarkers is determined within 3 hours of a suspected ischemicevent. In some embodiments, the levels of expression of the panel ofbiomarkers is determined at 3 or more hours after a suspected ischemicevent. In some embodiments, the levels of expression of the panel ofbiomarkers is determined within 6, 12, 18, 24, 36, 48 or 72 hours of asuspected ischemic event.

In some cases, the subject is asymptomatic, but may have a risk orpredisposition to experiencing ischemic stroke, e.g., based on genetics,familial history, a related disease condition, environment or lifestyle.In some embodiments, the patient has one or more vascular risk factors,e.g., hypertension, diabetes mellitus, hyperlipidemia, or tobaccosmoking. In some embodiments, the subject is non-Caucasian, for example,Asian, African-American or Latino or of Asian, African-American orLatino descent.

Patients presenting with clinical symptoms of lacunar infarcts ordiagnosed as having lacunar syndrome will also benefit from the presentdiagnostic gene expression profiling. Clinical symptoms of lacunarinfarcts include

-   -   pure motor hemiparesis    -   pure sensory stroke    -   sensorimotor stroke    -   dysarthria-clumsy hand syndrome    -   ataxic hemiparesis

Face, arm and leg involvement are characteristic of the first threelisted symptoms. A component of ataxia is also present in the last two.Patients with a lacunar syndrome typically have no aphasia, novisuospatial disturbance, no visual field defect, generally no cleardisturbance of brainstem function such as pupil abnormatities and eyemovement disturbances, and no decreased level of consciousness (as adirect effect rather than as a complication of the stroke) at any timeafter the stroke. See, Norrving, Pract Neurol (2008) 8:222-228.

3. Biomarkers Useful for the Prediction or Diagnosis of Lacunar Stroke,or for Distinguishing Lacunar Stroke from Non-Lacunar Stroke

Biomarkers useful for the prediction, diagnosis or confirmation of theoccurrence of lacunar stroke, or for distinguishing lacunar stroke fromnon-lacunar stroke (e.g., non-lacunar small deep infarct (SDI)) arelisted in Tables 3 and 4. Determination of the expression levels of aplurality of the biomarkers of Tables 3 and/or 4 can be performed forthe prediction, diagnosis or confirmation of the occurrence of lacunarstroke in conjunction with other biomarkers known in the art for theprediction, diagnosis or confirmation of the occurrence of ischemicstroke, SDI and/or lacunar stroke, in conjunction with other methodsknown in the art for the diagnosis of ischemic stroke, SDI and/orlacunar stroke, in conjunction with biomarkers described herein andknown in the art useful for determining the cause of ischemic strokeand/or in conjunction with methods known in the art for determining thecause of ischemic stroke.

Determination of the expression levels of a plurality of the biomarkersof Tables 3 and/or 4 can be performed for the prediction, diagnosis orconfirmation of the occurrence of stroke can also be performedindependently, e.g., to diagnose that a lacunar stroke has occurred, todistinguish lacunar stroke from non-lacunar stroke or non-lacunar SDI,or to determine the risk that a patient may suffer a lacunar stroke.

As appropriate, the expression levels of at least about 3, 5, 10, 15,20, 25, 30, 40, 50, 60, 70, 80 or more biomarkers from Table 3 or Table4 are determined. In some embodiments, the expression levels of aplurality of biomarkers in Table 3 or Table 4 are determined. In someembodiments, the expression levels of all listed biomarkers in Table 3or Table 4 are determined.

In some embodiments, the level of expression of biomarkers indicative ofthe occurrence of lacunar stroke is determined within 72 hours, forexample, within 60, 48, 36, 24, 12, 6 or 3 hours of a suspected ischemicevent. An increased expression level of one or more lacunarstroke-associated biomarkers of Table 3 selected from the groupconsisting of AKAP9, ALS2CR11, BNC2, BZRAP1, C18orf49, CALM1, CCDC114,CCDC78, CCL2, CCL3, CCL3L1, CCL3L3, CCL4, CHST2, CSF1, ERBB2, FAM179A,GBP4, GBR56, GRAMD3, GRHL2, GRK4, HLA-DRB4, ITIH4, KIAA1618, LAG3,LAIR2, LGR6, LOC100132181, LOC147646, LOC150622, LOC161527, OASL,PLEKHF1, PRKD2, PROCR, PRSS23, RASEF, RGNEF, RUNX3, SCAND2, SESN2,SLAMF7, SPON2, STAT1, SYNGR1, TRX21, TGFBR3, TMEM67, TSEN54, TTC12,TUBE1, UBA7, UTS2, and ZNF827, is correlative with or indicates that thepatient suffers from or is at risk of developing lacunar stroke. Adecreased expression level of one or more lacunar stroke-associatedbiomarkers of Table 3 selected from the group consisting of AGFG1, BTG1,CFDP1, CHML, CNPY2, FAM105A, FAM70B, FLJ13773, GATM, GTF2H2, GTF2H2B,HLA DQA1, IGHG1, IL18RAP, IL8, LOC254128, LRRC8B, MPZL3, N4BP2, PDXDC1,PHACTR1, QK1, RTKN2, SLC16A1, SOCS1, SPAG17, ST6GALNAC1, STK17B, STK4,STT3B, STX16, STX7, TBC1D12, TRIM4, UACA, UGCG, VAPA, and WHAMML2 iscorrelative with or indicates that the patient suffers from or is atrisk of developing lacunar stroke.

Conversely, a decreased expression level of one or more lacunarstroke-associated biomarkers of Table 3 selected from the groupconsisting of AKAP9, ALS2CR11, BNC2, BZRAP1, C18orf49, CALM1, CCDC114,CCDC78, CCL2, CCL3, CCL3L1, CCL3L3, CCL4, CHST2, CSF1, ERBB2, FAM179A,GBP4, GBR56, GRAMD3, GRHL2, GRK4, HLA-DRB4, ITIH4, KIAA1618, LAG3,LAIR2, LGR6, LOC100132181, LOC147646, LOC150622, LOC161527, OASL,PLEKHF1, PRKD2, PROCR, PRSS23, RASEF, RGNEF, RUNX3, SCAND2, SESN2,SLAMF7, SPON2, STAT1, SYNGR1, TRX21, TGFBR3, TMEM67, TSEN54, TTC12,TUBE1, UBA7, UTS2, and ZNF827, is correlative with or indicates that thepatient suffers from or is at risk of developing non-lacunar stroke.Similarly, an increased expression level of one or more lacunarstroke-associated biomarkers of Table 3 selected from the groupconsisting of AGFG1, BTG1, CFDP1, CHML, CNPY2, FAM105A, FAM70B,FLJ13773, GATM, GTF2H2, GTF2H2B, HLA DQA1, IGHG1, IL18RAP, IL8,LOC254128, LRRC8B, MPZL3, N4BP2, PDXDC1, PHACTR1, QK1, RTKN2, SLC16A1,SOCS1, SPAG17, ST6GALNAC1, STK17B, STK4, STT3B, STX16, STX7, TBC1D12,TRIM4, UACA, UGCG, VAPA, and WHAMML2 is correlative with or indicatesthat the patient suffers from or is at risk of developing non-lacunarstroke.

In some embodiments, the level of expression of biomarkers indicative ofthe occurrence of lacunar stroke is determined within 72 hours, forexample, within 60, 48, 36, 24, 12, 6 or 3 hours of a suspected ischemicevent. An increased expression level of one or more lacunarstroke-associated biomarkers of Table 4 selected from the groupconsisting of HLA-DRB4, TTC12, GBP4, UBA7, CCDC78, C18orf49, RASEF,TSEN54, RUNX3, PROCR, TGFBR3, PRSS23, CALM1, FAM179A, CCDC114, LGR6,SCAND2, LAIR2, CCL3, CCL3L1, CCL3L3, LAG3, CCL2, OASL, UTS2,LOC100132181 and ALS2CR11, is correlative with or indicates that thepatient suffers from or is at risk of developing lacunar stroke. Adecreased expression level of one or more lacunar stroke-associatedbiomarkers of Table 4 selected from the group consisting of STK4,LRRC8B, PDXDC1, LOC254128, L8, GTF2H2, UGCG, MPZL3, VAPA, STX7, FAM70B,QKI, CHML, FLJ13773, HLA-DQA1 is correlative with or indicates that thepatient suffers from or is at risk of developing lacunar stroke.

Conversely, a decreased expression level of one or more lacunarstroke-associated biomarkers of Table 4 selected from the groupconsisting of HLA-DRB4, TTC12, GBP4, UBA7, CCDC78, C18orf49, RASEF,TSEN54, RUNX3, PROCR, TGFBR3, PRSS23, CALM1, FAM179A, CCDC114, LGR6,SCAND2, LAIR2, CCL3, CCL3L1, CCL3L3, LAG3, CCL2, OASL, UTS2,LOC100132181 and ALS2CR11, is correlative with or indicates that thepatient suffers from or is at risk of developing non-lacunar stroke.Similarly, an increased expression level of one or more lacunarstroke-associated biomarkers of Table 4 selected from the groupconsisting of STK4, LRRC8B, PDXDC1, LOC254128, IL8, GTF2H2, UGCG, MPZL3,VAPA, STX7, FAM70B, QKI, CHML, FLJ13773, HLA-DQA1 is correlative with orindicates that the patient suffers from or is at risk of developingnon-lacunar stroke.

The overexpression or the underexpression of the biomarkers aredetermined with reference to a control level of expression. The controllevel of expression can be determined using any method known in the art.For example, the control level of expression can be from a population ofindividuals known to not have or be at risk for an ischemic event suchas lacunar stroke or can be determined with reference to a panel ofstably expressed reference biomarkers. Also, threshold levels ofexpression can be determined based on levels of expression inpredetermined populations (e.g., known to not have or be at risk for anischemic event such as lacunar stroke versus known to have or be at riskfor lacunar stroke). Overexpression or underexpression of a plurality ofbiomarkers from Table 3 or Table 4 that is at least about 1.2-fold,1.3-fold, 1.4-fold, 1.5-fold, 1.6-fold, 1.7-fold, 1.8-fold, 1.9-fold,2.0-fold, 2.1 fold, 2.2-fold, 2.3-fold, 2.4-fold, 2.5-fold, or more, incomparison to the expression levels of a plurality of stably expressedendogenous reference biomarkers, e.g., those listed in Table 1, iscorrelative with or indicates that the subject has experienced or is atrisk of experiencing a lacunar stroke. Overexpression or underexpressionof a plurality of biomarkers from Table 3 or Table 4 that is at leastabout 1.2-fold, 1.3-fold, 1.4-fold, 1.5-fold, 1.6-fold, 1.7-fold,1.8-fold, 1.9-fold, 2.0-fold, 2.1 fold, 2.2-fold, 2.3-fold, 2.4-fold,2.5-fold, or more, in comparison to the expression level of the samebiomarker in an individual or a population of individuals who have notexperienced a vascular event is correlative with or indicates that thesubject has experienced or is at risk of experiencing a lacunar stroke.

4. Biomarkers Useful for the Diagnosis of Cause of Non-Lacunar Stroke

In some embodiments, it may be determined that the suspected ischemicevent or SDI, or risk thereof, is due to non-lacunar causes.Accordingly, in some embodiments, the biological sample may be testedfor expression levels of biomarkers useful for distinguishing lacunarstroke from non-lacunar stroke, as well as for expression levels ofbiomarkers useful for the determination of the cause of ischemic stroke,particularly non-lacunar stroke. Measuring the expression levels ofbiomarkers to diagnose the cause of non-lacunar stroke can be performedconcurrently with (i.e., in parallel) or sequentially to measuring theexpression levels of biomarkers to distinguish the cause of stroke aslacunar or non-lacunar.

Biomarkers useful for the determination and diagnosis of the cause ofstroke are described, e.g., in co-owned and co-pending Application No.61/364,334 and 61/364,449, the disclosures of both of which are herebyincorporated herein by reference in their entirety for all purposes. Inaddition to evaluating the expression levels of a plurality ofbiomarkers useful for distinguishing lacunar from non-lacunar stroke,the expression levels of a plurality of biomarkers can be measured todetermine whether a suspected or predicted ischemic event iscardioembolic or atherosclerotic. Furthermore, the expression levels ofa plurality of biomarkers can be measured to determine if the cause ofstroke is due to carotid stenosis, atrial fibrillation or transientischemic attacks. Classification of stroke subtypes is known in the artand reviewed in, e.g., in Amarenco, et al., Cerebrovasc Dis (2009)27:493-501. Accordingly, in some embodiments, the expression levels ofat least about 3, 5, 10, 15, 20, 25, 30, 40, 50, 60, 70, 80, 85 or more,ischemic stroke-associated biomarkers are independently determined. Insome embodiments, the expression levels of all ischemicstroke-associated biomarkers in a panel are determined.

Overexpression or underexpression of a plurality ofischemic-stroke-associated biomarkers that is at least about 1.2-fold,1.3-fold, 1.4-fold, 1.5-fold, 1.6-fold, 1.7-fold, 1.8-fold, 1.9-fold,2.0-fold, 2.1 fold, 2.2-fold, 2.3-fold, 2.4-fold, 2.5-fold, 2.6-fold,2.7-fold, 2.8-fold, 2.9-fold, 3.0-fold, 3.1-fold, 3.2-fold, 3.3-fold,3.4-fold or 3.5-fold, or more, in comparison to the expression levels ofa plurality of stably expressed endogenous reference biomarkers, e.g.,those listed in Table 1, is correlative with or indicates that thesubject has experienced or is at risk of experiencing ischemic stroke.Overexpression or underexpression of a plurality of biomarkers that isat least about 1.2-fold, 1.3-fold, 1.4-fold, 1.5-fold, 1.6-fold,1.7-fold, 1.8-fold, 1.9-fold, 2.0-fold, 2.1 fold, 2.2-fold, 2.3-fold,2.4-fold, 2.5-fold, 2.6-fold, 2.7-fold, 2.8-fold, 2.9-fold, 3.0-fold,3.1-fold, 3.2-fold, 3.3-fold, 3.4-fold or 3.5-fold, or more, incomparison to the expression level of the same biomarker in anindividual or a population of individuals who have not experienced avascular or ischemic event is correlative with or indicates that thesubject has experienced or is at risk of experiencing ischemic stroke.

In various embodiments, the expression levels of a plurality of lacunarstroke associated gene are co-determined together with the expressionlevels of a plurality of genes useful in the determination of whether apatient has experienced or has a predisposition to experiencecardioembolic stroke (a.k.a., cardiac embolism, cardioembolismemboligenic heart disease). A cardioembolic stroke occurs when athrombus (clot) dislodges from the heart, travels through thecardiovascular system and lodges in the brain, first cutting off theblood supply and then often causing a hemorrhagic bleed. In someembodiments an increased expression level of one or more ischemicstroke-associated biomarkers selected from the group consisting of IRF6(NM_006147), ZNF254 (NM_203282), GRM5 (NM_000842///NM_001143831), EXT2(NM_000401///NM_207122), AP3S2 (NM_005829///NR_023361), PIK3C2B(NM_002646), ARHGEF5 (NM_005435), COL13A1(NM_001130103///NM_005203///NM_080798///NM_080799///NM_080800///NM_080801///NM_080802///NM_080803///NM_080804///NM_080805///NM_080806///NM_080807///NM_080808///NM_080809///NM_080810///NM_080811///NM_080812///NM_080813///NM_080814///NM_080815),PTPN20A///PTPN20B(NM_001042357///NM_001042358///NM_001042359///NM_001042360///NM_001042361///NM_001042362///NM_(—)001042363///NM_001042364///NM_001042365///NM_001042387///NM_001042389///NM_001042390///NM_001042391///NM_001042392///NM_001042393///NM_001042394///NM_001042395///NM_001042396///NM_001042397///NM_015605),LHFP (NM_005780), BANK1 (NM_001083907////NM_001127507///NM_017935),HLA-DOA (NM_002119), EBF1 (NM_024007), TMEM19 (NM_018279), LHFP(NM_005780), FCRL1 (NM_001159397///NM_001159398///NM_052938), OOEP(NM_001080507) and LRRC37A3 (NM_199340) is correlative with or indicatesthat the patient has experienced or is at risk for cardioembolic stroke.In some embodiments, a decreased expression level of one or moreischemic stroke-associated biomarkers selected from the group consistingof LOC284751 (NM_001025463), CD46(NM_002389///NM_153826///NM_172350///NM_172351///NM_172352///NM_172353///NM_172354///NM_172355///NM_172356///NM_172357///NM_172358///NM_172359///NM_172360///NM_172361),ENPP2 (NM_001040092///NM_001130863///NM_006209), C19orf28(NM_001042680///NM_021731///NM_174983), TSKS (NM_021733), CHURC1(NM_145165), ADAMTSL4 (NM_019032///NM_025008), FLJ40125 (NM_001080401),CLEC18A (NM_001136214///NM_182619), ARHGEF12 (NM_015313), C16orf68(NM_024109), TFDP1 (NM_007111///NR_026580) and GSTK1(NM_001143679///NM_001143680///NM_001143681///NM_015917) is correlativewith or indicates that the patient has experienced or is at risk forcardioembolic stroke.

In various embodiments, the expression levels of a plurality of lacunarstroke associated gene are co-determined together with the expressionlevels of a plurality of genes useful in the determination of whether apatient has experienced or has a predisposition to experience carotidstenosis. Carotid stenosis is a narrowing or constriction of the innersurface (lumen) of the carotid artery, usually caused byatherosclerosis. An inflammatory buildup of plaque can narrow thecarotid artery and can be a source of embolization. Emboli break offfrom the plaque and travel through the circulation to blood vessels inthe brain, causing ischemia that can either be temporary (e.g., atransient ischemic attack), or permanent resulting in a thromboembolicstroke (a.k.a., atherothrombosis, large-artery atherosclerosis,atherosclerosis with stenosis). In some embodiments, an increasedexpression level of one or more ischemic stroke-associated biomarkersselected from the group consisting of NT5E (NM_002526), CLASP2(NM_015097), GRM5 (NM_000842///NM_001143831), PROCR (NM_006404), ARHGEF5(NM_005435), AKR1C3 (NM_003739), COL13A1(NM_001130103///NM_005203///NM_080798///NM_080799///NM_080800///NM_080801///NM_080802///NM_080803///NM_080804///NM_080805///NM_080806///NM_080807///NM_080808///NM_080809///NM_080810///NM_080811///NM_080812///NM_080813///NM_080814///NM_080815),LHFP (NM_005780), RNF7 (NM_014245///NM_183237), CYTH3 (NM_004227), EBF1(NM_024007), RANBP10 (NM_020850), PRSS35 (NM_153362), C12orf42(NM_001099336///NM_198521) and LOC100127980(XM_001720119///XM_001722650) is correlative with or indicates that thepatient has experienced or is at risk for carotid stenosis. In someembodiments, a decreased expression level of one or more ischemicstroke-associated biomarkers selected from the group consisting ofFLJ31945 (XM_001714983///XM_001716811///XM_001718431), LOC284751(NM_001025463), LOC100271832 (NR_027097), MTBP (NM_022045), ICAM4(NM_001039132///NM_001544///NM_022377), SHOX2(NM_001163678////NM_003030///NM_006884), DOPEY2 (NM_005128), CMBL(NM_138809), LOC146880 (NR_026899///NR_027487), SLC20A1 (NM_005415),SLC6A19 (NM_001003841), ARHGEF12 (NM_015313), C16orf68 (NM_024109),GIPC2 (NM_017655) and LOC100144603 (NR_021492) is correlative with orindicates that the patient has experienced or is at risk for carotidstenosis.

In various embodiments, the expression levels of a plurality of lacunarstroke associated gene are co-determined together with the expressionlevels of a plurality of genes useful in the determination of whether apatient has experienced or has a predisposition to experience atrialfibrillation. Atrial fibrillation (AF or A-fib) is the most commoncardiac arrhythmia and involves the two upper chambers (atria) of theheart fibrillating (i.e., quivering) instead of a coordinatedcontraction. In some instances, cardioembolic stroke can occur as aresult of atrial fibrillation. Cardioembolic stroke can be a downstreamresult of atrial fibrillation in that stagnant blood in the fibrillatingatrium can form a thrombus that then embolises to the cerebralcirculation, blocking arterial blood flow and causing ischaemic injury.In some embodiments, an increased expression level of one or moreischemic stroke-associated biomarkers selected from the group consistingof SMC1A (NM_006306), SNORA68 (NR_000012), GRLF1 (NM_004491), SDC4(NM_002999), HIPK2(NM_001113239///NM_022740///XM_001716827///XM_925800), LOC100129034(NR_027406///XR_079577), CMTM1(NM_052999///NM_181268///NM_181269///NM_181270///NM_181271///NM_181272///NM_181283///NM_(—)181296)and TTC7A (NM_020458) is correlative with or indicates that the patienthas experienced or is at risk for atrial fibrillation. In someembodiments, a decreased expression level of one or more ischemicstroke-associated biomarkers selected from the group consisting ofLRRC43 (NM_001098519///NM_152759), MIF///SLC2A11(NM_001024938///NM_001024939///NM_002415///NM_030807), PER3 (NM_016831),PPIE (NM_006112///NM_203456///NM_203457), COL13A1(NM_001130103///NM_005203///NM_080798///NM_080799///NM_080800///NM_080801///NM_080802///NM_080803///NM_080804///NM_080805///NM_080806///NM_080807///NM_080808///NM_080809///NM_080810///NM_080811///NM_008812///NM_080813///NM_080814///NM_080815),DUSP16 (NM_030640), BRUNOL6 (NM_052840), GPR176 (NM_007223), C6orf164(NR_026784) and MAP3K7IP1 (NM_006116///NM_153497) is correlative with orindicates that the patient has experienced or is at risk for atrialfibrillation.

In various embodiments, the expression levels of a plurality of lacunarstroke associated gene are co-determined together with the expressionlevels of a plurality of genes useful in the determination of whether apatient has experienced or has a predisposition to experience transientischemic attacks (TIA). A transient ischemic attack is a change in theblood supply to a particular area of the brain, resulting in briefneurologic dysfunction that persists, by definition, for less than 24hours. If symptoms persist longer, then it is categorized as a stroke.In some embodiments, an increased expression level of one or moreTIA-associated biomarkers selected from the group consisting of GABRB2(NM_000813///NM_021911), ELAVL3 (NM_001420///NM_032281), COL1A1(NM_000088), SHOX2 (NM_003030///NM_006884), TWIST1 (NM_000474), DPPA4(NM_018189), DKFZP434P211 (NR_003714), WIT1 (NM_015855///NR_023920),SOX9 (NM_000346), DLX6 (NM_005222), ANXA3 (NM_005139), EPHA3(NM_005233///NM_182644), SOX11 (NM_003108), SLC26A8(NM_052961///NM_138718), CCRL1 (NM_016557///NM_178445), FREM2(NM_207361), STOX2 (NM_020225), ZNF479(NM_033273///XM_001714591///XM_001719979), LOC338862 (NR_038878.1),ASTN2 (NM_014010///NM_198186///NM_198187///NM_198188), FOLH1(NM_001014986///NM_004476), SNX31 (NM_152628), KREMEN1(NM_001039570///NM_001039571), ALS2CR11 (NM_152525), FIGN (NM_018086),RORB (NM_006914), LOC732096 (XM_001720784///XM_001725388///XR_016064),GYPA (NM_002099), ALPL (NM_000478///NM_001127501), LHX2 (NM_004789),GALNT5 (NM_014568), SRD5A2L2 (NM_001010874), GALNT14 (NM_024572), OVOL2(NM_021220), BMPR1B (NM_001203), UNC5B (NM_170744), ODZ2(NM_001080428///NM_001122679), RASAL2 (NM_004841///NM_170692), SHOX(NM_000451///NM_006883), C19orf59 (NM_174918), ZNF114 (NM_153608),SRGAP1 (NM_020762), ELAVL2 (NM_004432), NCRNA00032(XM_376821///XM_938938), LOC440345 (XR_015786), FLJ30375(XM_001724993///XM_001725199///XM_001725628), TFPI(NM_001032281///NM_006287), PTGR1 (NM_012212), ROBO1(NM_002941///NM_133631), NR2F2 (NM_021005), GRM5(NM_000842///NM_001143831), LUM (NM_002345), FLJ39051 (NR_033839.1),COL1A2 (NM_000089), CASP5(NM_001136109///NM_001136110///NM_001136111///NM_001136112///NM_004347//),OPCML (NM_001012393///NM_002545), TTC6 (NM_001007795), TFAP2B(NM_003221), CRISP2(NM_001142407///NM_001142408///NM_001142417///NM_001142435///NM_003296),SOX11 (NM_003108), ANKRD30B(XM_001716904///XM_001717561///XM_001717810), SCN2A(NM_001040142///NM_001040143///NM_021007), MYNN (NM_018657), FOXA2(NM_021784///NM_153675), DKFZP434B061 (XR_015528///XR_040812), LOC645323(NR_015436///NR_024383///NR_024384///XR_041118///XR_041119///XR_041120),SNIP (NM_025248), LOC374491 (NR_002815), ADAM30 (NM_021794), SIX3(NM_005413), FLJ36144 (XR_040632///XR_040633///XR_040634), CARD8(NM_014959), RP1-127L4.6 (NM_001010859), FAM149A(NM_001006655///NM_015398), B3GAT2 (NM_080742), SPOCK3(NM_001040159///NM_016950), ITGBL1 (NM_004791), IQGAP3 (NM_178229),C7orf45 (NM_145268), ZNF608 (NM_020747), LOC375010 (XR_041271), LRP2(NM_004525), TGFB2 (NM_001135599///NM_003238), SHOX2(NM_003030///NM_006884), HOXC4///HOXC6(NM_004503///NM_014620///NM_153633///NM_153693), ELTD1 (NM_022159),FAM182B///RP13-401N8.2(XM_001132551///XM_001133521///XM_001718365///XM_933752), LIFR(NM_001127671///NM_002310), FOLH1 (NM_001014986///NM_004476), EHF(NM_012153), NDST3 (NM_004784), BRUNOL5 (NM_021938), LOC728460(XM_001128581///XM_001129498///XM_001723364), PDE1A(NM_001003683///NM_005019), POU2AF1 (NM_006235), FAT1 (NM_005245),PCDH11X///PCDH11Y(NM_014522///NM_032967///NM_032968///NM_032969///NM_032971///NM_032972),FLJ37786 (XR_041472///XR_041473), SLC22A4 (NM_003059), DHRS13(NM_144683), MEG3 (NR_002766///NR_003530///NR_003531), PIWIL1(NM_004764), LOC203274 (AL117607.1///BC080605.1),LOC100133920///LOC286297(NR_024443///XM_001714612///XM_372109///XM_933054///XM_933058), DMRT1(NM_021951), ADM (NM_001124), VWA3B (NM_144992), GAFA3(XM_001715321///XM_001722922///XM_001723636), HESX1 (NM_003865),ADAMDEC1 (NM_014479), CAV1 (NM_001753), LAMB4 (NM_007356), TPTE(NM_199259///NM_199260///NM_199261), PPP1R1C (NM_001080545), HPSE(NM_001098540///NM_006665), AIM2 (NM_004833), RUNDC3B(NM_001134405///NM_001134406///NM_138290), CARD16(NM_001017534///NM_052889), FAM124A (NM_145019), MGC39584(XR_017735///XR_017787///XR_041937), OSM (NM_020530), RFX2(NM_000635///NM_134433), MYBPC1(NM_002465///NM_206819///NM_2068206820///NM_206821), LTBR (NM_002342),C18orf2 (NM_031416///NR_023925///NR_023926///NR_023927///NR_023928),SNRPN(NM_003097///NM_022805///NM_022806///NM_022807///NM_022808///NR_001289),FLJ36031 (NM_175884), IL1B (NM_000576), TRPM1 (NM_002420), OSTCL(NM_145303), MAPK14 (NM_001315///NM_139012///NM_139013///NM_139014),KCNJ15///LOC100131955(NM_002243///NM_170736///NM_170737///XM_001713900///XM_001715532///XM_0),FIGN (NM_018086), HNT (NM_001048209///NM_016522), S100A12 (NM_005621),CHIT1 (NM_003465), C7orf53 (NM_001134468///NM_182597), FAM13A1(NM_001015045///NM_014883), GNAO1 (NM_020988///NM_138736), MAPK14(NM_001315///NM_139012///NM_139013///NM_139014), FAM55D(NM_001077639///NM_017678), PRKD2(NM_001079880///NM_001079881///NM_001079882///NM_016457), LIMK2(NM_001031801///NM_005569///NM_016733), C18orf54 (NM_173529), IGFBP5(NM_000599), EVI1 (NM_001105077///NM_001105078///NM_005241), PLSCR1(NM_021105), FOXC1 (NM_001453), LOC646627 (NM_001085474), ZNF462(NM_021224), CNTLN (NM_001114395///NM_017738), ZNF438(NM_001143766///NM_001143767///NM_001143768///NM_001143769///NM_001143770),DEFB105A///DEFB105B (NM_001040703///NM_152250), LOC340017 (NR_026992.1),C1orf67 (NM_144989), ACSL1 (NM_001995), ADH1B (NM_000668),SLC2A14///SLC2A3 (NM_006931///NM_153449), IL1B (NM_000576), ST3GAL4(NM_006278///XM_001714343///XM_001726541///XM_001726562), UBE2J1(NM_016021), PNPLA3 (NM_025225) and PAPPA (NM_002581) is correlativewith or indicates that the patient has experienced or is at risk forTIA. In some embodiments, a decreased expression level of one or moreTIA-associated biomarkers selected from the group consisting ofNBPF10///RP11-94I2.2 (NM_001039703///NM_183372///XM_001722184), SFXN1(NM_022754), SPIN3 (NM_001010862), UNC84A (NM_001130965///NM_025154),OLFM2 (NM_058164), PPM1K (NM_152542), P2RY10 (NM_014499///NM_198333),ZNF512B (NM_020713), MORF4L2(NM_001142418///NM_001142419///NM_001142420///NM_001142421///NM_001142422),GIGYF2 (NM_001103146///NM_001103147///NM_001103148///NM_015575), ERAP2(NM_001130140///NM_022350), SLFN13 (NM_144682), LOC401431(XR_040272///XR_040273///XR_040274///XR_040275), MED6 (NM_005466),BAIAP2L1///LOC100128461(NM_018842///XM_001722656///XM_001724217///XM_001724858), LNPEP(NM_005575///NM_175920), MBNL1(NM_021038///NM_207292///NM_207293///NM_207294///NM_207295///NM_207296),NOS3 (NM_000603), MCF2L (NM_001112732///NM_024979), KIAA1659(XM_001723799///XM_001725435///XM_001726785), SCAMP5 (NM_138967),LOC648921 (XM_001715629///XM_001720571///XR_018520), ANAPC5(NM_001137559///NM_016237), SPON1 (NM_006108), FUS (NM_004960), GPR22(NM_005295), GAL3ST4 (NM_024637), METTL3 (NM_019852), LOC100131096(XM_001720907///XM_001726205///XM_001726705), FAAH2 (NM_174912), SMURF2(NM_022739), SNRPN(NM_003097///NM_022805///NM_022806///NM_022807///NM_022808///NR_001289),FBLN7 (NM_001128165///NM_153214), GLS (NM_014905), G3BP1(NM_005754///NM_198395), RCAN3 (NM_013441), EPHX2 (NM_001979), DIP2C(NM_014974), CCDC141 (NM_173648), CLTC (NM_004859), FOSB(NM_001114171///NM_006732), CACNA1I (NM_001003406///NM_021096), UNQ6228(XM_001725293///XM_001725359///XM_001726164), ATG9B (NM_173681), AK5(NM_012093///NM_174858), RBM14 (NM_006328), MAN1C1 (NM_020379), HELLS(NM_018063), EDAR (NM_022336), SLC3A1 (NM_000341), ZNF519 (NM_145287),LOC100130070///LOC100130775///LOC100131787///LOC100131905///LOC100132291///LOC100132488///RPS27(NM_001030///XM_001721002///XM_001722161///XM_001722965///XM_001723889//),ZC3H12B (NM_001010888), IQGAP2 (NM_006633), SOX8 (NM_014587), WHDC1L2(XM_926785), TNPO1 (NM_002270///NM_153188), TNFRSF21 (NM_014452), TSHZ2(NM_173485), DMRTC1///DMRTC1B (NM_001080851///NM_033053), GSTM1(NM_000561///NM_146421), GSTM2 (NM_000848///NM_001142368), PNMA6A(NM_032882), CAND1 (NM_018448), CCND3(NM_001136017///NM_001136125///NM_001136126///NM_001760), GSTM1(NM_000561///NM_146421), and GUSBL2(NR_003660///XR_(—)042150///XR_042151) is correlative with or indicatesthat the patient has experienced or is at risk for TIA.

5. Comparison to a Control Level of Expression

The expression levels of the lacunar stroke-associated biomarkers arecompared to a control level of expression. As appropriate, the controllevel of expression can be the expression level of the same lacunarstroke-associated biomarker in an otherwise healthy individual (e.g., inan individual who has not experienced and/or is not at risk ofexperiencing a vascular event, e.g., TIA, ischemic stroke or a smalldeep infarct). In some embodiments, the control level of expression isthe expression level of a plurality of stably expressed endogenousreference biomarkers, as described herein and/or known in the art. Insome embodiments, the control level of expression is a predeterminedthreshold level of expression of the same lacunar stroke-associatedbiomarker, e.g., based on the expression level of the biomarker in apopulation of otherwise healthy individuals. In some embodiments, theexpression level of the lacunar stroke-associated biomarker in the testsubject and the expression level of the lacunar stroke-associatedbiomarker in an otherwise healthy individual are normalized to (i.e.,divided by), e.g., the expression levels of a plurality of stablyexpressed endogenous reference biomarkers.

In some embodiments, the overexpression or underexpression of a lacunarstroke associated biomarker is determined with reference to theexpression of the same lacunar stroke associated biomarker in anotherwise healthy individual. For example, a healthy or normal controlindividual has not experienced and/or is not at risk of experiencingischemic stroke, transient ischemic attack or a small deep infarction.The healthy or normal control individual generally has not experienced avascular event (e.g., TIA, ischemic stroke, myocardial infarction,peripheral vascular disease, or venous thromboembolism) and does nothave cerebral vascular disease. The healthy or normal control individualgenerally does not have one or more vascular risk factors (e.g.,hypertension, diabetes mellitus, hyperlipidemia, or tobacco smoking). Asappropriate, the expression levels of the target lacunarstroke-associated biomarker in the healthy or normal control individualcan be normalized (i.e., divided by) the expression levels of aplurality of stably expressed endogenous reference biomarkers.

In some embodiments, the overexpression or underexpression of a lacunarstroke associated biomarker is determined with reference to one or morestably expressed endogenous reference biomarkers. Internal controlbiomarkers or endogenous reference biomarkers are expressed at the sameor nearly the same expression levels in the blood of patients withstroke or TIAs or SDIs as compared to control patients. Targetbiomarkers are expressed at higher or lower levels in the blood of thestroke or TIA or SDI patients. The expression levels of the targetbiomarker to the reference biomarker are normalized by dividing theexpression level of the target biomarker to the expression levels of aplurality of endogenous reference biomarkers. The normalized expressionlevel of a target biomarker can be used to predict the occurrence orlack thereof of stroke or TIA or SDI, and/or the cause of stroke or TIAor SDI.

In some embodiments, the expression level of the lacunarstroke-associated biomarker from a patient suspected of having orexperiencing lacunar stroke and from a control patient are normalizedwith respect to the expression levels of a plurality of stably expressedendogenous genes. The expression levels of the normalized expression ofthe lacunar stroke-associated biomarker can be compared to theexpression levels of the normalized expression of the same lacunarstroke-associated biomarker in a control patient. The determined foldchange in expression=normalized expression of target biomarker inlacunar stroke patient/normalized expression of target biomarker incontrol patient. Overexpression or underexpression of the normalizedlacunar stroke-associated biomarker in the lacunar stroke patient by atleast about 1.2-fold, 1.3-fold, 1.4-fold, 1.5-fold, 1.6-fold, 1.7-fold,1.8-fold, 1.9-fold, 2.0-fold, 2.1 fold, 2.2-fold, 2.3-fold, 2.4-fold,2.5-fold, 2.6-fold, 2.7-fold, 2.8-fold, 2.9-fold, 3.0-fold, 3.1-fold,3.2-fold, 3.3-fold, 3.4-fold or 3.5-fold, or more, in comparison to theexpression levels of the normalized lacunar stroke-associated biomarkerin a healthy control patient is correlative with or indicates that thelacunar stroke or SDI patient has experienced or is at risk ofexperiencing lacunar stroke.

In some embodiments, the control level of expression is a predeterminedthreshold level. The threshold level can correspond to the level ofexpression of the same lacunar stroke-associated biomarker in anotherwise healthy individual or a population of otherwise healthyindividuals, optionally normalized to the expression levels of aplurality of endogenous reference biomarkers. After expression levelsand normalized expression levels of the lacunar stroke-associatedbiomarkers are determined in a representative number of otherwisehealthy individuals and individuals predisposed to experiencing SDI orlacunar stroke, normal and lacunar stroke expression levels of thelacunar stroke-associated biomarkers can be maintained in a database,allowing for determination of threshold expression levels indicative ofthe presence or absence of risk to experience lacunar stroke or theoccurrence of lacunar stroke. If the predetermined threshold level ofexpression is with respect to a population of normal control patients,then overexpression or underexpression of the lacunar stroke-associatedbiomarker (usually normalized) in the stroke patient by at least about1.2-fold, 1.3-fold, 1.4-fold, 1.5-fold, 1.6-fold, 1.7-fold, 1.8-fold,1.9-fold, 2.0-fold, 2.1 fold, 2.2-fold, 2.3-fold, 2.4-fold, 2.5-fold,2.6-fold, 2.7-fold, 2.8-fold, 2.9-fold, 3.0-fold, 3.1-fold, 3.2-fold,3.3-fold, 3.4-fold or 3.5-fold, or more, in comparison to the thresholdlevel is correlative with or indicates that the lacunar stroke patienthas experienced or is at risk of experiencing lacunar stroke. If thepredetermined threshold level of expression is with respect to apopulation of patients known to have experienced lacunar stroke or knownto be at risk for experiencing lacunar stroke, then an expression levelin the patient suspected of experiencing lacunar stroke that isapproximately equal to the threshold level (or overexpressed orunderexpressed greater than the threshold level of expression), iscorrelative with or indicates that the lacunar stroke or SDI patient hasexperienced or is at risk of experiencing lacunar stroke.

With respect to the endogenous reference biomarkers used for comparison,preferably, Exemplary endogenous reference biomarkers that find use arelisted in Table 1, below. Further suitable endogenous referencebiomarkers are published, e.g., in Stamova, et al., BMC Medical Genomics(2009) 2:49. In some embodiments, the expression levels of a pluralityof endogenous reference biomarkers are determined as a control. In someembodiments, the expression levels of at least about 2, 3, 4, 5, 6, 7,8, 9, 10, 15, 20, 25, 30, 35, or more, endogenous reference biomarkers,e.g., as listed in Table 1 or known in the art, are determined as acontrol.

TABLE 1 The 38 endogenous reference biomarkers stably expressed in bloodfor use in normalization and as control levels. Table 1. Stablyexpressed endogenous reference biomarkers RefSeq RefSeq Probe Set IDGene Symbol Gene Title GenBank ID UniGene ID Transcript ID Protein ID201499_s_at USP7 ubiquitin specific peptidase NM_003470.1 Hs.706830NM_003470 NP_003461 7 (herpes virus-associated) 202501_at MAPRE2microtubule-associated NM_014268.1 Hs.532824 NM_001143826 ///NP_001137298 /// protein, RP/EB family, NM_001143827 /// NP_001137299/// member 2 NM_014268 /// NP_055083 NR_026570 202573_at CSNK1G2 caseinkinase 1, gamma 2 AL530441 Hs.651905 NM_001319 NP_001310 203280_at SAFB2scaffold attachment factor NM_014649.1 Hs.655392 NM_014649 NP_055464 B2204842_x_at PRKAR2A protein kinase, cAMP- BC002763.1 Hs.631923 NM_004157NP_004148 dependent, regulatory, type II, alpha 206138_s_at PI4KBphosphatidylinositol 4- NM_002651.1 Hs.632465 NM_002651 NP_002642kinase, catalytic, beta 207159_x_at CRTC1 CREB regulated NM_025021.1Hs.371096 NM_001098482 /// NP_001091952 /// transcription coactivator 1NM_015321 NP_056136 208630_at HADHA hydroxyacyl-Coenzyme A AI972144Hs.516032 NM_000182 NP_000173 dehydrogenase/3- ketoacyl-Coenzyme Athiolase/enoyl-Coenzyme A hydratase (trifunctional protein), alphasubunit 208786_s_at MAP1LC3B microtubule-associated AF183417.1 Hs.356061NM_022818 NP_073729 protein 1 light chain 3 beta 209192_x_at KAT5K(lysine) acetyltransferase BC000166.2 Hs.397010 NM_006388 /// NP_006379/// 5 NM_182709 /// NP_874368 /// NM_182710 NP_874369 210474_s_at CDC2L1/// cell division cycle 2-like 1 U04819.1 Hs.651228 NM_024011 ///NP_076916 /// CDC2L2 (PITSLRE proteins) /// cell NM_033486 /// NP_277021/// division cycle 2-like 2 NM_033487 /// NP_277022 /// (PITSLREproteins) NM_033488 /// NP_277023 /// NM_033489 /// NP_277024 ///NM_033492 /// NP_277027 /// NM_033493 /// NP_277028 /// NM_033529NP_277071 211040_x_at GTSE1 G-2 and S-phase BC006325.1 Hs.386189NM_016426 NP_057510 expressed 1 211289_x_at CDC2L1 /// cell divisioncycle 2-like 1 AF067524.1 Hs.651228 NM_024011 /// NP_076916 /// CDC2L2(PITSLRE proteins) /// cell NM_033486 /// NP_277021 /// division cycle2-like 2 NM_033487 /// NP_277022 /// (PITSLRE proteins) NM_033488 ///NP_277023 /// NM_033489 /// NP_277024 /// NM_033492 /// NP_277027 ///NM_033493 /// NP_277028 /// NM_033529 NP_277071 213311_s_at TCF25transcription factor 25 BF000251 Hs.415342 NM_014972 NP_055787 (basichelix-loop-helix) 214665_s_at CHP calcium binding protein AK000095.1Hs.406234 NM_007236 NP_009167 P22 215063_x_at LRRC40 leucine rich repeatAL390149.1 Hs.147836 NM_017768 NP_060238 containing 40 215200_x_at — —AK022362.1 Hs.663419 — — 215568_x_at hCG_2003956 /// hCG2003956 ///AL031295 Hs.533479 NM_007260 /// NP_009191 LYPLA2 /// lysophospholipaseII /// NR_001444 LYPLA2P1 lysophospholipase II pseudogene 1 216038_x_atDAXX death-domain associated BE965715 Hs.336916 NM_001141969 ///NP_001135441 /// protein NM_001141970 /// NP_001135442 /// NM_001350 ///NP_001341 NR_024517 217393_x_at UBE2NL ubiquitin-conjugating AL109622Hs.585177 NM_001012989 NP_001013007 enzyme E2N-like 217549_at — —AW574933 Hs.527860 — — 217672_x_at EIF1 eukaryotic translation BF114906Hs.150580 NM_005801 NP_005792 initiation factor 1 217938_s_at KCMF1potassium channel NM_020122.1 Hs.654968 NM_020122 NP_064507 modulatoryfactor 1 218378_s_at PRKRIP1 PRKR interacting protein 1 NM_024653.1Hs.406395 NM_024653 NP_078929 (IL11 inducible) 218571_s_at CHMP4Achromatin modifying NM_014169.1 Hs.279761 NM_014169 NP_054888 protein 4A219074_at TMEM184C transmembrane protein NM_018241.1 Hs.203896 NM_018241NP_060711 184C 220052_s_at TINF2 TERF1 (TRF1)-interacting NM_012461.1Hs.496191 NM_001099274 /// NP_001092744 /// nuclear factor 2 NM_012461NP_036593 220411_x_at PODNL1 podocan-like 1 NM_024825.1 Hs.448497NM_001146254 /// NP_001139726 /// NM_001146255 /// NP_001139727 ///NM_024825 NP_079101 221813_at FBXO42 F-box protein 42 AI129395 Hs.522384NM_018994 NP_061867 222207_x_at LOC441258 Williams Beuren syndromeAK024602.1 Hs.711232 — — chromosome region 19 pseudogene 222733_x_atRRP1 ribosomal RNA processing BC000380.1 Hs.110757 NM_003683 NP_003674 1homolog (S. cerevisiae) 224667_x_at C10orf104 chromosome 10 openAK023981.1 Hs.426296 NM_173473 NP_775744 reading frame 104 224858_atZDHHC5 zinc finger, DHHC-type AK023130.1 Hs.27239 NM_015457 NP_056272containing 5 225403_at C9orf23 chromosome 9 open AL528391 Hs.15961NM_148178 /// NP_680544 /// reading frame 23 NM_148179 NP_680545226253_at LRRC45 leucine rich repeat BE965418 Hs.143774 NM_144999NP_659436 containing 45 227651_at NACC1 nucleus accumbens AI498126Hs.531614 NM_052876 NP_443108 associated 1, BEN and BTB (POZ) domaincontaining 232190_x_at LOC100133445 /// hypothetical AI393958 Hs.132272NR_026927 /// — LOC115110 LOC100133445 /// XR_036887 /// hypotheticalprotein XR_038144 LOC115110 49878_at PEX16 peroxisomal biogenesisAA523441 Hs.100915 NM_004813 /// NP_004804 /// factor 16 NM_057174NP_476515

In some embodiments, the expression levels of the endogenous referencebiomarkers GAPDH, ACTB, B2M, HMBS and PPIB are determined as a control.In some embodiments, the expression levels of 2, 3, 4, 5, 6, 7, 8, 9,10, 15, 20, 25, or more, endogenous reference biomarkers selected fromthe group consisting of USP7, MAPRE2, CSNK1G2, SAFB2, PRKAR2A, PI4 KB,CRTC1, HADHA, MAP1LC3B, KAT5, CDC2L1///CDC2L2, GTSE1, CDC2L1///CDC2L2,TCF25, CHP, LRRC40, hCG_2003956///LYPLA2///LYPLA2P1, DAXX, UBE2NL, EIF1,KCMF1, PRKRIP1, CHMP4A, TMEM184C, TINF2, PODNL1, FBXO42, LOC441258,RRP1, C10orf104, ZDHHC5, C9orf23, LRRC45, NACC1,LOC100133445///LOC115110, PEX16 are determined as a control.

Biomarkers indicative of lacunar stroke have levels of expression thatare at least about 1.2-fold, 1.3-fold, 1.4-fold, 1.5-fold, 1.6-fold,1.7-fold, 1.8-fold, 1.9-fold, 2.0-fold, 2.1 fold, 2.2-fold, 2.3-fold,2.4-fold, 2.5-fold, 2.6-fold, 2.7-fold, 2.8-fold, 2.9-fold, 3.0-fold,3.1-fold, 3.2-fold, 3.3-fold, 3.4-fold or 3.5-fold, or more, incomparison to the expression levels of a plurality of stably expressedendogenous reference biomarkers, e.g., the geometric average expressionlevel of the evaluated endogenous reference biomarkers, e.g., 2, 3, 4,5, 6, 7, 8, 9, 10, 15, 20, 25, 30, 35, or more biomarkers listed inTable 1.

6. Methods of Detecting Biomarkers

Gene expression may be measured using any method known in the art. Oneof skill in the art will appreciate that the means of measuring geneexpression is not a critical aspect of the invention. The expressionlevels of the biomarkers can be detected at the transcriptional ortranslational (i.e., protein) level.

In some embodiments, the expression levels of the biomarkers aredetected at the transcriptional level. A variety of methods of specificDNA and RNA measurement using nucleic acid hybridization techniques areknown to those of skill in the art (see, Sambrook, supra and Ausubel,supra) and may be used to detect the expression of the genes set forthin Tables 3 and 4. Some methods involve an electrophoretic separation(e.g., Southern blot for detecting DNA, and Northern blot for detectingRNA), but measurement of DNA and RNA can also be carried out in theabsence of electrophoretic separation (e.g., by dot blot). Southern blotof genomic DNA (e.g., from a human) can be used for screening forrestriction fragment length polymorphism (RFLP) to detect the presenceof a genetic disorder affecting a polypeptide of the invention. Allforms of RNA can be detected, including, e.g., message RNA (mRNA),microRNA (miRNA), ribosomal RNA (rRNA) and transfer RNA (tRNA).

The selection of a nucleic acid hybridization format is not critical. Avariety of nucleic acid hybridization formats are known to those skilledin the art. For example, common formats include sandwich assays andcompetition or displacement assays. Hybridization techniques aregenerally described in Hames and Higgins Nucleic Acid Hybridization, APractical Approach, IRL Press (1985); Gall and Pardue, Proc. Natl. Acad.Sci. U.S.A., 63:378-383 (1969); and John et al. Nature, 223:582-587(1969).

Detection of a hybridization complex may require the binding of asignal-generating complex to a duplex of target and probepolynucleotides or nucleic acids. Typically, such binding occurs throughligand and anti-ligand interactions as between a ligand-conjugated probeand an anti-ligand conjugated with a signal. The binding of the signalgeneration complex is also readily amenable to accelerations by exposureto ultrasonic energy.

The label may also allow indirect detection of the hybridizationcomplex. For example, where the label is a hapten or antigen, the samplecan be detected by using antibodies. In these systems, a signal isgenerated by attaching fluorescent or enzyme molecules to the antibodiesor in some cases, by attachment to a radioactive label (see, e.g.,Tijssen, “Practice and Theory of Enzyme Immunoassays,” LaboratoryTechniques in Biochemistry and Molecular Biology, Burdon and vanKnippenberg Eds., Elsevier (1985), pp. 9-20).

The probes can be labeled either directly, e.g., with isotopes,chromophores, lumiphores, chromogens, or indirectly, such as withbiotin, to which a streptavidin complex may later bind. Thus, thedetectable labels used in the assays of the present invention can beprimary labels (where the label comprises an element that is detecteddirectly or that produces a directly detectable element) or secondarylabels (where the detected label binds to a primary label, e.g., as iscommon in immunological labeling). Typically, labeled signal nucleicacids are used to detect hybridization. Complementary nucleic acids orsignal nucleic acids may be labeled by any one of several methodstypically used to detect the presence of hybridized polynucleotides. Themost common method of detection is the use of autoradiography with ³H,¹²⁵I, ³⁵S, ¹⁴C, or ³²P-labeled probes or the like.

Other labels include, e.g., ligands that bind to labeled antibodies,fluorophores, chemiluminescent agents, enzymes, and antibodies which canserve as specific binding pair members for a labeled ligand. Anintroduction to labels, labeling procedures and detection of labels isfound in Polak and Van Noorden Introduction to Immunocytochemistry, 2nded., Springer Verlag, NY (1997); and in Haugland Handbook of FluorescentProbes and Research Chemicals, a combined handbook and cataloguePublished by Molecular Probes, Inc. (1996).

In general, a detector which monitors a particular probe or probecombination is used to detect the detection reagent label. Typicaldetectors include spectrophotometers, phototubes and photodiodes,microscopes, scintillation counters, cameras, film and the like, as wellas combinations thereof. Examples of suitable detectors are widelyavailable from a variety of commercial sources known to persons of skillin the art. Commonly, an optical image of a substrate comprising boundlabeling moieties is digitized for subsequent computer analysis.

Most typically, the amount of RNA is measured by quantifying the amountof label fixed to the solid support by binding of the detection reagent.Typically, the presence of a modulator during incubation will increaseor decrease the amount of label fixed to the solid support relative to acontrol incubation which does not comprise the modulator, or as comparedto a baseline established for a particular reaction type. Means ofdetecting and quantifying labels are well known to those of skill in theart.

In preferred embodiments, the target nucleic acid or the probe isimmobilized on a solid support. Solid supports suitable for use in theassays of the invention are known to those of skill in the art. As usedherein, a solid support is a matrix of material in a substantially fixedarrangement.

For example, in one embodiment of the invention, microarrays are used todetect the pattern of gene expression. Microarrays provide one methodfor the simultaneous measurement of the expression levels of largenumbers of genes. Each array consists of a reproducible pattern of aplurality of nucleic acids (e.g., a plurality of nucleic acids thathybridize to a plurality of the genes set forth in Tables 3 and 4)attached to a solid support. In one embodiment, the array contains aplurality of nucleic acids that hybridize to a plurality of the geneslisted in Table 3. In one embodiment, the array contains a plurality ofnucleic acids that hybridize to a plurality of the genes listed in Table4. In one embodiment, the array further contains a plurality of nucleicacids that hybridize to a plurality of genes useful for diagnosingischemic stroke, cardioembolic stroke, carotid stenosis, atrialfibrillation or transient ischemic attacks, as described herein or knownin the art. Labeled RNA or DNA is hybridized to complementary probes onthe array and then detected by laser scanning. Hybridization intensitiesfor each probe on the array are determined and converted to aquantitative read-out of relative gene expression levels in ischemia(e.g., stroke or SDI (lacunar or non-lacunar) or transient ischemicattacks).

In some embodiments, a sample is obtained from a subject, total mRNA isisolated from the sample and is converted to labeled cRNA and thenhybridized to an array. Relative transcript levels are calculated byreference to appropriate controls present on the array and in thesample. See Mahadevappa and Warrington, Nat. Biotechnol. 17, 1134-1136(1999).

A variety of automated solid-phase assay techniques are alsoappropriate. For instance, very large scale immobilized polymer arrays(VLSIPS™), available from Affymetrix, Inc. (Santa Clara, Calif.) can beused to detect changes in expression levels of a plurality of genesinvolved in the same regulatory pathways simultaneously. See, Tijssen,supra., Fodor et al. (1991) Science, 251: 767-777; Sheldon et al. (1993)Clinical Chemistry 39(4): 718-719, and Kozal et al. (1996) NatureMedicine 2(7): 753-759. Integrated microfluidic systems and otherpoint-of-care diagnostic devices available in the art also find use.See, e.g., Liu and Mathies, Trends Biotechnol. (2009) 27(10):572-81 andTothill, Semin Cell Dev Biol (2009) 20(1):55-62. Microfluidics systemsfor use in detecting levels of expression of a plurality of nucleicacids are available, e.g., from NanoString Technologies, on the internetat nanostring.com.

Detection can be accomplished, for example, by using a labeled detectionmoiety that binds specifically to duplex nucleic acids (e.g., anantibody that is specific for RNA-DNA duplexes). One preferred exampleuses an antibody that recognizes DNA-RNA heteroduplexes in which theantibody is linked to an enzyme (typically by recombinant or covalentchemical bonding). The antibody is detected when the enzyme reacts withits substrate, producing a detectable product. Coutlee et al. (1989)Analytical Biochemistry 181:153-162; Bogulavski (1986) et al. J.Immunol. Methods 89:123-130; Prooijen-Knegt (1982) Exp. Cell Res.141:397-407; Rudkin (1976) Nature 265:472-473, Stollar (1970) Proc.Nat'l Acad. Sci. USA 65:993-1000; Ballard (1982) Mol. Immunol.19:793-799; Pisetsky and Caster (1982) Mol. Immunol. 19:645-650; Viscidiet al. (1988) J. Clin. Microbial. 41:199-209; and Kiney et al. (1989) J.Clin. Microbiol. 27:6-12 describe antibodies to RNA duplexes, includinghomo and heteroduplexes. Kits comprising antibodies specific for DNA:RNAhybrids are available, e.g., from Digene Diagnostics, Inc. (Beltsville,Md.).

In addition to available antibodies, one of skill in the art can easilymake antibodies specific for nucleic acid duplexes using existingtechniques, or modify those antibodies that are commercially or publiclyavailable. In addition to the art referenced above, general methods forproducing polyclonal and monoclonal antibodies are known to those ofskill in the art (see, e.g., Paul (3rd ed.) Fundamental Immunology RavenPress, Ltd., NY (1993); Coligan, et al., Current Protocols inImmunology, Wiley Interscience (1991-2008); Harlow and Lane, Antibodies:A Laboratory Manual Cold Spring Harbor Press, NY (1988); Harlow andLane, Using Antibodies, Cold Spring Harbor Press, NY (1999); Stites etal. (eds.) Basic and Clinical Immunology (4th ed.) Lange MedicalPublications, Los Altos, Calif., and references cited therein; GodingMonoclonal Antibodies: Principles and Practice (2d ed.) Academic Press,New York, N.Y., (1986); and Kohler and Milstein Nature 256: 495-497(1975)). Other suitable techniques for antibody preparation includeselection of libraries of recombinant antibodies in phage or similarvectors (see, Huse et al. Science 246:1275-1281 (1989); and Ward et al.Nature 341:544-546 (1989)). Specific monoclonal and polyclonalantibodies and antisera will usually bind with a dissociation constant(K_(D)) of at least about 0.1 μM, preferably at least about 0.01 μM orbetter, and most typically and preferably, 0.001 μM or better.

The nucleic acids used in this invention can be either positive ornegative probes. Positive probes bind to their targets and the presenceof duplex formation is evidence of the presence of the target. Negativeprobes fail to bind to the suspect target and the absence of duplexformation is evidence of the presence of the target. For example, theuse of a wild type specific nucleic acid probe or PCR primers may serveas a negative probe in an assay sample where only the nucleotidesequence of interest is present.

The sensitivity of the hybridization assays may be enhanced through useof a nucleic acid amplification system that multiplies the targetnucleic acid being detected. Examples of such systems include thepolymerase chain reaction (PCR) system, in particular RT-PCR or realtime PCR, and the ligase chain reaction (LCR) system. Other methodsrecently described in the art are the nucleic acid sequence basedamplification (NASBA, Cangene, Mississauga, Ontario) and Q BetaReplicase systems. These systems can be used to directly identifymutants where the PCR or LCR primers are designed to be extended orligated only when a selected sequence is present. Alternatively, theselected sequences can be generally amplified using, for example,nonspecific PCR primers and the amplified target region later probed fora specific sequence indicative of a mutation. High throughput multiplexnucleic acid sequencing or “deep sequencing” to detect capturedexpressed biomarker genes also finds use. High throughput sequencingtechniques are known in the art (e.g., 454 Sequencing on the internet at454.com).

An alternative means for determining the level of expression of thenucleic acids of the present invention is in situ hybridization. In situhybridization assays are well known and are generally described inAngerer et al., Methods Enzymol. 152:649-660 (1987). In an in situhybridization assay, cells, preferentially human cells, are fixed to asolid support, typically a glass slide. If DNA is to be probed, thecells are denatured with heat or alkali. The cells are then contactedwith a hybridization solution at a moderate temperature to permitannealing of specific probes that are labeled. The probes are preferablylabeled with radioisotopes or fluorescent reporters.

In other embodiments, quantitative RT-PCR is used to detect theexpression of a plurality of the genes set forth in Tables 3 and 4. Inone embodiment, quantitative RT-PCR is used to detect a plurality of thegenes listed in Table 3. In one embodiment, quantitative RT-PCR is usedto detect a plurality of the genes listed in Table 4. In one embodiment,quantitative RT-PCR is used to further detect a plurality of the genesuseful for the diagnosis of ischemic stroke, cardioembolic stroke,carotid stenosis, atrial fibrillation and/or transient ischemic attacks,as described herein and known in the art. A general overview of theapplicable technology can be found, for example, in A-Z of QuantitativePCR, Bustin, ed., 2004, International University Line; Quantitative PCRProtocols, Kochanowski and Reischl, eds., 1999, Humana Press; ClinicalApplications of PCR, Lo, ed., 2006, Humana Press; PCR Protocols: A Guideto Methods and Applications (Innis et al. eds. (1990)) and PCRTechnology: Principles and Applications for DNA Amplification (Erlich,ed. (1992)). In addition, amplification technology is described in U.S.Pat. Nos. 4,683,195 and 4,683,202. Methods for multiplex PCR, known inthe art, are applicable to the present invention.

Accordingly, in one embodiment of the invention provides a reactionmixture comprising a plurality of polynucleotides which specificallyhybridize (e.g., primers) to a plurality of nucleic acid sequences ofthe genes set forth in Tables 3 and 4. In some embodiments, theinvention provides a reaction mixture comprising a plurality ofpolynucleotides which specifically hybridize (e.g., primers) to aplurality of nucleic acid sequences of the genes set forth in Table 3.In some embodiments, the invention provides a reaction mixturecomprising a plurality of polynucleotides which specifically hybridize(e.g., primers) to a plurality of nucleic acid sequences of the genesset forth in Table 4. In some embodiments, the invention provides areaction mixture further comprising a plurality of polynucleotides whichspecifically hybridize (e.g., primers) to a plurality of nucleic acidsequences of the genes useful for the diagnosis of ischemic stroke,cardioembolic stroke, carotid stenosis, atrial fibrillation and/ortransient ischemic attacks, as described herein and known in the art. Insome embodiments, the reaction mixture is a PCR mixture, for example, amultiplex PCR mixture.

This invention relies on routine techniques in the field of recombinantgenetics. Generally, the nomenclature and the laboratory procedures inrecombinant DNA technology described below are those well-known andcommonly employed in the art. Standard techniques are used for cloning,DNA and RNA isolation, amplification and purification. Generallyenzymatic reactions involving DNA ligase, DNA polymerase, restrictionendonucleases and the like are performed according to the manufacturer'sspecifications. Basic texts disclosing the general methods of use inthis invention include Sambrook et al., Molecular Cloning, A LaboratoryManual (3rd ed. 2001); Kriegler, Gene Transfer and Expression: ALaboratory Manual (1990); and Current Protocols in Molecular Biology(Ausubel et al., eds., 1994-2008, Wiley Interscience)).

For nucleic acids, sizes are given in either kilobases (kb) or basepairs (bp). These are estimates derived from agarose or acrylamide gelelectrophoresis, from sequenced nucleic acids, or from published DNAsequences. For proteins, sizes are given in kilodaltons (kDa) or aminoacid residue numbers. Proteins sizes are estimated from gelelectrophoresis, from sequenced proteins, from derived amino acidsequences, or from published protein sequences.

Oligonucleotides that are not commercially available can be chemicallysynthesized according to the solid phase phosphoramidite triester methodfirst described by Beaucage & Caruthers, Tetrahedron Letts. 22:1859-1862(1981), using an automated synthesizer, as described in Van Devanter et.al., Nucleic Acids Res. 12:6159-6168 (1984). Purification ofoligonucleotides is by either native acrylamide gel electrophoresis orby anion-exchange HPLC as described in Pearson & Reanier, J. Chrom.255:137-149 (1983).

In some embodiments, the expression level of the biomarkers describedherein are detected at the translational or protein level. Detection ofproteins is well known in the art, and methods for protein detectionknown in the art find use. Exemplary assays for determining theexpression levels of a plurality of proteins include, e.g., ELISA, flowcytometry, mass spectrometry (e.g., MALDI or SELDI), surface plasmonresonance (e.g., BiaCore), microfluidics and other biosensortechnologies. See, e.g., Tothill, Semin Cell Dev Biol (2009)20(1):55-62.

7. Lacunar Stroke and Ischemia Reference Profiles

The invention also provides expression reference profiles useful for thediagnosis of lacunar stroke or for distinguishing lacunar stroke fromnon-lacunar stroke. The gene expression reference profiles compriseinformation correlating the expression levels of a plurality of lacunarstroke-associated genes (i.e., a plurality of the genes set forth inTables 3 and 4) to lacunar stroke (versus non-lacunar stroke). In oneembodiment, the lacunar stroke reference profile correlates theexpression levels of a plurality of the genes listed in Table 3 to theoccurrence or risk of lacunar stroke. In one embodiment, the lacunarstroke reference profile correlates the expression levels of a pluralityof the genes listed in Table 4 to the occurrence or risk of lacunarstroke. In one embodiment, the lacunar stroke reference profilecorrelates the expression levels of a plurality of the genes listed inTable 3 to the occurrence or risk of non-lacunar stroke (e.g.,cardioembolic stroke, carotid stenosis, atrial fibrillation, transientischemic attacks, or other causes). In one embodiment, the lacunarstroke reference profile correlates the expression levels of a pluralityof the genes listed in Table 4 to the occurrence or risk of non-lacunarstroke (e.g., cardioembolic stroke, carotid stenosis, atrialfibrillation, transient ischemic attacks, or other causes). The profilescan conveniently be used to diagnose, monitor and prognose the cause ofan ischemic event.

One embodiment of the invention provides a lacunar stroke geneexpression reference profile for subjects who have experienced or are atrisk for experiencing lacunar stroke. Accordingly, the lacunar strokereference profile correlates the expression levels of a plurality of thegenes selected from Table 3. For example, an expression profileexhibiting an increase in expression of a plurality of the followinggenes: AKAP9, ALS2CR11, BNC2, BZRAP1, C18orf49, CALM1, CCDC114, CCDC78,CCL2, CCL3, CCL3L1, CCL3L3, CCL4, CHST2, CSF1, ERBB2, FAM179A, GBP4,GBR56, GRAMD3, GRHL2, GRK4, HLA-DRB4, ITIH4, KIAA1618, LAG3, LAIR2,LGR6, LOC100132181, LOC147646, LOC150622, LOC161527, OASL, PLEKHF1,PRKD2, PROCR, PRSS23, RASEF, RGNEF, RUNX3, SCAND2, SESN2, SLAMF7, SPON2,STAT1, SYNGR1, TRX21, TGFBR3, TMEM67, TSEN54, TTC12, TUBE1, UBA7, UTS2,and ZNF827, when compared to the control level, and/or a decrease inexpression of a plurality of the following genes: AGFG1, BTG1, CFDP1,CHML, CNPY2, FAM105A, FAM70B, FLJ13773, GATM, GTF2H2, GTF2H2B, HLA-DQA1,IGHG1, L18RAP, IL8, LOC254128, LRRC8B, MPZL3, N4BP2, PDXDC1, PHACTR1,QK1, RTKN2, SLC16A1, SOCS1, SPAG17, ST6GALNAC1, STK17B, STK4, STT3B,STX16, STX7, TBC1D12, TRIM4, UACA, UGCG, VAPA, and WHAMML2, whencompared to the control level is a reference profile for a subject whohas experienced or is at risk for lacunar stroke.

One embodiment of the invention provides a lacunar stroke geneexpression reference profile for subjects who have experienced or are atrisk for experiencing lacunar stroke. Accordingly, the lacunar strokereference profile correlates the expression levels of a plurality of thegenes selected from Table 4. For example, an expression profileexhibiting an increase in expression of a plurality of the followinggenes: HLA-DRB4, TTC12, GBP4, UBA7, CCDC78, C18orf49, RASEF, TSEN54,RUNX3, PROCR, TGFBR3, PRSS23, CALM1, FAM179A, CCDC114, LGR6, SCAND2,LAIR2, CCL3, CCL3L1, CCL3L3, LAG3, CCL2, OASL, UTS2, LOC100132181 andALS2CR11, when compared to the control level, and/or a decrease inexpression of a plurality of the following genes: STK4, LRRC8B, PDXDC1,LOC254128, L8, GTF2H2, UGCG, MPZL3, VAPA, STX7, FAM70B, QKI, CHML,FLJ13773, HLA-DQA1, when compared to the control level is a referenceprofile for a subject who has experienced or is at risk for lacunarstroke.

One embodiment of the invention further provides an ischemia referenceprofile for subjects who have experienced or are at risk forexperiencing stroke, regardless of cause. Accordingly, the ischemiareference profile correlates the expression levels of a plurality ofischemic stroke-associated genes. For example, an expression profileexhibiting an increase in expression of a plurality of the followinggenes: PGM5, CCDC144C///LOC100134159, LECT2, SHOX, TBX5, SNIP, RBMS3,P704P, THSD4, FAT3, SNRPN, GLYATL1, GADL1, CXADR, OVOL2, RNF141, CLEC4E,BXDC5, UNC5B, TIMP2, ASTN2, FLJ35934, ANKRD28, CCDC144A, TIMM8A,ALDOAP2, LDB3, PTPRD, LOC729222///PPFIBP1, CCRL1, FCRL4, ELAVL2, PRTG,DLX6, SCD5, GABRB2, GYPA, PHTF1, CKLF, CKLF, RRAGD, CLEC4E, CKLF, FGD4,CPEB2, LOC100290882, UBXN2B, ENTPD1, BST1, LTB4R, F5, IFRD1, KIAA0319,CHMP1B, MCTP1, VNN3, AMN1, LAMP2, FCHO2, ZNF608, REM2, QKI, RBM25, FAR2,ST3GAL6, HNRNPH2, GAB1, UBR5, VAPA, LOC283027, LOC344595, RPL22,LOC100129488 and MCTP1 when compared to the control level, and/or adecrease in expression of a plurality of the following genes: SPTLC3,DKRZP434L187, SPIB, HNRNPUL2, FOXA2, RPL22 and SH3GL3 when compared tothe control level is a reference profile for a subject who hasexperienced or is at risk for stroke.

One embodiment of the invention further provides an ischemia referenceprofile for subjects who have experienced or are at risk forexperiencing cardioembolic stroke. Accordingly, the ischemia referenceprofile correlates the expression levels of a plurality of the genescorrelative for or associated with cardioembolic stroke. For example, anexpression profile exhibiting an increase in expression of a pluralityof the following genes: IRF6, ZNF254, GRM5, EXT2, AP3S2, PIK3C2B,ARHGEF5, COL13A1, PTPN20A///PTPN20B, LHFP, BANK1, HLA-DOA, EBF1, TMEM19,LHFP, FCRL1, OOEP and LRRC37A3 when compared to the control level,and/or a decrease in expression of a plurality of the following genes:LOC284751, CD46, ENPP2, C19orf28, TSKS, CHURC1, ADAMTSL4, FLJ40125,CLEC18A, ARHGEF12, C16orf68, TFDP1 and GSTK1 when compared to thecontrol level is a reference profile for a subject who has experiencedor is at risk for a cardioembolic stroke.

One embodiment of the invention further provides an ischemia referenceprofile for subjects who have experienced or are at risk forexperiencing carotid stenosis and atherosclerotic stroke. Accordingly,the ischemia reference profile correlates the expression levels of aplurality of the genes correlative for or associated with carotidstenosis and atherosclerotic stroke. For example, an expression profileexhibiting an increase in expression of a plurality of the followinggenes: NT5E, CLASP2, GRM5, PROCR, ARHGEF5, AKR1C3, COL13A1, LHFP, RNF7,CYTH3, EBF1, RANBP10, PRSS35, C12orf42 and LOC100127980 when compared tothe control level, and/or a decrease in expression of a plurality of thefollowing genes: FLJ31945, LOC284751, LOC100271832, MTBP, ICAM4, SHOX2,DOPEY2, CMBL, LOC146880, SLC20A1, SLC6A19, ARHGEF12, C16orf68, GIPC2when compared to the control level is a reference profile for a subjectwho has experienced or is at risk for carotid stenosis andatherothrombotic stroke.

One embodiment of the invention further provides an ischemia referenceprofile for subjects who have experienced or are at risk forexperiencing atrial fibrillation. Accordingly, the ischemia referenceprofile correlates the expression levels of a plurality of the genescorrelative for or associated with atrial fibrillation. For example, anexpression profile exhibiting an increase in expression of a pluralityof the following genes: SMC1A, SNORA68, GRLF1, SDC4, HIPK2,LOC100129034, CMTM1 and TTC7A when compared to the control level, and/ora decrease in expression of a plurality of the following genes: LRRC43,MIF///SLC2A11, PER3, PPIE, COL13A1, DUSP16, LOC100129034, BRUNOL6,GPR176, C6orf164 and MAP3K7IP1 when compared to the control level is areference profile for a subject who has experienced or is at risk foratrial fibrillation.

One embodiment of the invention further provides an ischemia referenceprofile for subjects who have experienced or are at risk forexperiencing transient ischemic attacks. Accordingly, the ischemiareference profile correlates the expression levels of a plurality of thegenes correlative for or associated with transient ischemic attacks. Forexample, an expression profile exhibiting an increase in expression of aplurality of the following genes: GABRB2, ELAVL3, COL1A1, SHOX2, GABRB2,TWIST1, DPPA4, DKFZP434P211, WIT1, SOX9, DLX6, ANXA3, EPHA3, SOX11,SLC26A8, CCRL1, FREM2, STOX2, ZNF479, LOC338862, ASTN2, FOLH1, SNX31,KREMEN1, ZNF479, ALS2CR11, FIGN, RORB, LOC732096, GYPA, ALPL, LHX2,GALNT5, SRD5A2L2, GALNT14, OVOL2, BMPR1B, UNC5B, ODZ2, ALPL, RASAL2,SHOX, C19orf59, ZNF114, SRGAP1, ELAVL2, NCRNA00032, LOC440345, FLJ30375,TFPI, PTGR1, ROBO1, NR2F2, GRM5, LUM, FLJ39051, COL1A2, CASP5, OPCML,TTC6, TFAP2B, CRISP2, SOX11, ANKRD30B, FLJ39051, SCN2A, MYNN, FOXA2,DKFZP434B061, LOC645323, SNIP, LOC645323, LOC374491, ADAM30, SIX3,FLJ36144, CARD8, KREMEN1, RP1-127L4.6, FAM149A, B3GAT2, SPOCK3, G30,ITGBL1, IQGAP3, C7orf45, ZNF608, LOC375010, LRP2, TGFB2, SHOX2,HOXC4///HOXC6, ELTD1, FAM182B///RP13-401N8.2, PRO0478, LIFR, FOLH1, EHF,NDST3, BRUNOL5, LOC728460, PDE1A, POU2AF1, FAT1, PCDH11X///PCDH11Y,FLJ37786, SLC22A4, DHRS13, EHF, MEG3, PIWIL1, LOC203274,LOC100133920///LOC286297, DMRT1, ADM, VWA3B, GAFA3, HESX1, ADAMDEC1,CAV1, LAMB4, TPTE, PPP1R1C, HPSE, AIM2, RUNDC3B, CARD16, FAM124A,MGC39584, OSM, RFX2, MYBPC1, LTBR, C18orf2, SNRPN, FLJ36031, IL1B,TRPM1, OSTCL, MAPK14, KCNJ15///LOC100131955, FIGN, HNT, S100A12, CHIT1,C7orf53, FAM13A1, GNAO1, MAPK14, FAM55D, PRKD2, LIMK2, C18orf54, IGFBP5,EVI1, PLSCR1, FOXC1, LOC646627, ZNF462, CNTLN, ZNF438,DEFB105A///DEFB105B, LOC340017, C1orf67, ACSL1, ADH1B, SLC2A14///SLC2A3,IL1B, ST3GAL4, UBE2J1, PNPLA3 and PAPPA when compared to the controllevel, and/or a decrease in expression of a plurality of the followinggenes: NBPF10///RP11-94I2.2, SFXN1, SPIN3, UNC84A, OLFM2, PPM1K, P2RY10,ZNF512B, MORF4L2, GIGYF2, ERAP2, SLFN13, LOC401431, MED6,BAIAP2L1///LOC100128461, LNPEP, MBNL1, NOS3, MCF2L, KIAA1659, SCAMP5,LOC648921, ANAPC5, SPON1, FUS, GPR22, GAL3ST4, METTL3, LOC100131096,FAAH2, SMURF2, SNRPN, FBLN7, GLS, G3BP1, RCAN3, EPHX2, DIP2C, CCDC141,CLTC, FOSB, CACNA1I, UNQ6228, ATG9B, AK5, SPIN3, RBM14, SNRPN, MAN1C1,HELLS, EDAR, SLC3A1, ZNF519,LOC100130070///LOC100130775///LOC100131787///LOC100131905///LOC100132291///LOC100132488///RPS27,ZC3H12B, IQGAP2, SOX8, WHDC1L2, TNPO1, TNFRSF21, TSHZ2,DMRTC1///DMRTC1B, GSTM1, GSTM2, PNMA6A, CAND1, CCND3, GSTM1, GUSBL2 whencompared to the control level is a reference profile for a subject whohas experienced or is at risk for transient ischemic attack.

The reference profiles can be entered into a database, e.g., arelational database comprising data fitted into predefined categories.Each table, or relation, contains one or more data categories incolumns. Each row contains a unique instance of data for the categoriesdefined by the columns. For example, a typical database for theinvention would include a table that describes a sample with columns forage, gender, reproductive status, expression profile and so forth.Another table would describe a disease: symptoms, level, sampleidentification, expression profile and so forth. In one embodiment, theinvention matches the experimental sample to a database of referencesamples. The database is assembled with a plurality of different samplesto be used as reference samples. An individual reference sample in oneembodiment will be obtained from a patient during a visit to a medicalprofessional. Information about the physiological, disease and/orpharmacological status of the sample will also be obtained through anymethod available. This may include, but is not limited to, expressionprofile analysis, clinical analysis, medical history and/or patientinterview. For example, the patient could be interviewed to determineage, sex, ethnic origin, symptoms or past diagnosis of disease, and theidentity of any therapies the patient is currently undergoing. Aplurality of these reference samples will be taken. A single individualmay contribute a single reference sample or more than one sample overtime. One skilled in the art will recognize that confidence levels inpredictions based on comparison to a database increase as the number ofreference samples in the database increases.

The database is organized into groups of reference samples. Eachreference sample contains information about physiological,pharmacological and/or disease status. In one aspect the database is arelational database with data organized in three data tables, one wherethe samples are grouped primarily by physiological status, one where thesamples are grouped primarily by disease status and one where thesamples are grouped primarily by pharmacological status. Within eachtable the samples can be further grouped according to the two remainingcategories. For example the physiological status table could be furthercategorized according to disease and pharmacological status.

As will be appreciated by one of skill in the art, the present inventionmay be embodied as a method, data processing system or program products.Accordingly, the present invention may take the form of data analysissystems, methods, analysis software, etc. Software written according tothe present invention is to be stored in some form of computer readablemedium, such as memory, hard-drive, DVD ROM or CD ROM, or transmittedover a network, and executed by a processor. The present invention alsoprovides a computer system for analyzing physiological states, levels ofdisease states and/or therapeutic efficacy. The computer systemcomprises a processor, and memory coupled to said processor whichencodes one or more programs. The programs encoded in memory cause theprocessor to perform the steps of the above methods wherein theexpression profiles and information about physiological, pharmacologicaland disease states are received by the computer system as input.Computer systems may be used to execute the software of an embodiment ofthe invention (see, e.g., U.S. Pat. No. 5,733,729).

8. Providing Appropriate Treatment and Prevention Regimes to Patient

Upon a positive determination or confirmation that a patient hasexperienced a stroke, and a determination of the cause of stroke, e.g.,using the biomarkers provided herein, the methods further provide forthe step of prescribing, providing or administering a regime for theprophylaxis or treatment of ischemic stroke or SDI. By diagnosing theoccurrence and/or the cause of stroke using the biomarkers describedherein, a patient can rapidly receive treatment that is tailored to andappropriate for the type of stroke that has been experienced, or thatthe patient is at risk of experiencing.

If the expression levels of the plurality of lacunar stroke-associatedbiomarkers indicate the occurrence or risk of lacunar stroke, a positivediagnosis of lacunar stroke can be supported or confirmed using methodsknown in the art. For example, the patient can be subject to clinicalevaluation (e.g., determination of one or more of the lacunar syndromes,including (1) Pure motor stroke/hemiparesis, (2) Ataxic hemiparesis, (3)Dysarthria/clumsy hand, (4) Pure sensory stroke, and (5) Mixedsensorimotor stroke), radiologic imaging, retinal imaging, evaluation ofblood-brain barrier permeability, evidence of microhemorrhage and bloodendothelial markers (e.g., (homocysteine, intercellular adhesionmolecule 1 (ICAM1), thrombomodulin (TM), tissue factor (TF) and tissuefactor pathway inhibitor (TFPI); Hassan, et al., Brain (2003) 126(Pt2):424-32; and Hassan, et al., Brain. (2004) 127(Pt 1):212-9). Upon apositive diagnosis of lacunar stroke, the patient may be administeredtissue plasminogen activator within three hours of an ischemic event ifthe patient is without contraindications (i.e. a bleeding diathesis suchas recent major surgery or cancer with brain metastases). High doseaspirin may be given within 48 hours of an ischemic event. For long termprevention of recurrence, medical regimens may be aimed towardscorrecting the underlying risk factors for lacunar infarcts such ashypertension, diabetes mellitus and cigarette smoking.

In cases where non-lacunar stroke is indicated, further evaluation tothe cause of non-lacunar stroke can be performed.

For example, if the expression levels of the plurality of ischemicstroke-associated biomarkers indicate the occurrence or risk of ischemicstroke, a positive diagnosis of ischemic stroke can be supported orconfirmed using methods known in the art. For example, the patient canbe subject to MRI imaging of brain and vessels, additional blood tests,EKG, and/or echocardiogram.

If the expression levels of the plurality of biomarkers indicate theoccurrence or risk of cardioembolic stroke, the patient can beprescribed or administered a regime of an anticoagulant. Exemplaryanticoagulants include aspirin, heparin, warfarin, and dabigatran.

If the expression levels of the plurality of biomarkers indicate theoccurrence or risk of carotid stenosis, the patient can be prescribed oradministered a regime of an anti-platelet drug. The most frequently usedanti-platelet medication is aspirin. An alternative to aspirin is theanti-platelet drug clopidogrel (Plavix). Some studies indicate thataspirin is most effective in combination with another anti-plateletdrug. In some embodiments, the patient is prescribed a combination oflow-dose aspirin and the anti-platelet drug dipyridamole (Aggrenox), toreduce blood clotting. Ticlopidine (Ticlid) is another anti-plateletmedication that finds use. Patients having a moderately or severelynarrowed neck (carotid) artery, may require or benefit from carotidendarterectomy. This preventive surgery clears carotid arteries of fattydeposits (atherosclerotic plaques) to prevent a first or subsequentstrokes. In some embodiments, the patient may require or benefit fromcarotid angioplasty, or stenting. Carotid angioplasty involves using aballoon-like device to open a clogged artery and placing a small wiretube (stent) into the artery to keep it open.

If the expression levels of the plurality of biomarkers indicate theoccurrence or risk of atrial fibrillation, the patient can be prescribeda regime of an anti-coagulant (to prevent stroke) and/or apharmacological agent to achieve rate control. Exemplary anticoagulantsinclude aspirin, heparin, warfarin, and dabigatran. Exemplary ratecontrol drugs include beta blockers (e.g., metoprolol, atenolol,bisoprolol), non-dihydropyridine calcium channel blockers (e.g.,diltiazem or verapamil), and cardiac glycosides (e.g., digoxin).

If the expression levels of the plurality of biomarkers indicate theoccurrence or risk of transient ischemic attacks (TIA), the patient canbe prescribed a regime of medications and/or life-style adjustments(e.g., diet, exercise, stress) to minimize risk factors can berecommended, including reducing blood pressure and cholesterol levels,and controlling diabetes. Several medications to decrease the likelihoodof a stroke after a transient ischemic attack. The medication selectedwill depend on the location, cause, severity and type of TIA, if TIA hasoccurred. For example, the patient may be prescribed a regime of ananti-platelet drug. The most frequently used anti-platelet medication isaspirin. An alternative to aspirin is the anti-platelet drug clopidogrel(Plavix). Some studies indicate that aspirin is most effective incombination with another anti-platelet drug. In some embodiments, thepatient is prescribed a combination of low-dose aspirin and theanti-platelet drug dipyridamole (Aggrenox), to reduce blood clotting.Ticlopidine (Ticlid) is another anti-platelet medication that finds useto prevent or reduce the risk of stroke in patients who have experiencedTIA. In some embodiments, the patient may be prescribed a regime of ananticoagulant. Exemplary anticoagulants include aspirin, heparin,warfarin, and dabigatran. Patients having a moderately or severelynarrowed neck (carotid) artery, may require or benefit from carotidendarterectomy to clear carotid arteries of fatty deposits(atherosclerotic plaques) before another TIA or stroke can occur. Insome embodiments, the patient may require or benefit from carotidangioplasty, or stenting.

The present methods for determining whether a patient has experienced orhas a predisposition to experience lacunar stroke can be confirmed,complemented by, and/or used in conjunction with diagnostic tests knownin the art for diagnosing lacunar stroke. For example, the presentmethods can be performed in conjunction with additional diagnostic basedon imaging or ultrasound techniques. In various embodiments, the presentmethods are performed in conjunction with one or more diagnostic testsselected from the group consisting of X-ray computed tomography (CT),magnetic resonance imaging (MRI) brain scanning, vascular imaging of thehead and neck with doppler or magnetic resonance angiography (MRA), CTangiography (CTA), electrocardiogram (e.g., EKG or ECG), cardiacultrasound and cardiac monitoring. In various embodiments, the patientis subjected to cardiac monitoring for at least 2 days, e.g., for 2-30days or for 7-21 days, e.g., for 2, 5, 7, 10, 12, 14, 18, 20, 21, 25,28, 30, or more days, as appropriate. An infarction located in asubcortical region of the brain is associated with or correlated with adiagnosis of lacunar stroke. An infarction located in a cortical regionof the brain, e.g., in regions of the penetrating arteries, e.g., basalganglia, thalamus, internal capsule, corona radiata and/or pons, isassociated with or correlated with a diagnosis of non-lacunar stroke. Insome embodiments, the size of the infarction is determined.

9. Solid Supports and Kits

The invention further provides, a solid support comprising a pluralityof nucleic acid probes that hybridize to a plurality (e.g., two or more,or all) of the genes set forth in Tables 3 and 4, and optionallyTable 1. For example, the solid support can be a microarray attached toa plurality of nucleic acid probes that hybridize to a plurality (e.g.,two or more, or all) of the genes set forth in Tables 3 and 4, andoptionally Table 1. In various embodiments, the solid supports areconfigured to exclude genes not associated with or useful to thediagnosis, prediction or confirmation of a lacunar stroke, or for strokegenerally. For example, genes that are overexpressed or underexpressedless than 1.2-fold in subjects with lacunar stroke in comparison to acontrol level of expression can be excluded from the present solidsupports. In some embodiments, genes that are overexpressed orunderexpressed less than 1.2-fold in subjects with ischemic stroke,including lacunar stroke, cardioembolic stroke, atherothrombotic stroke,TIA, and stroke subsequent to atrial fibrillation, in comparison to acontrol level of expression can be excluded from the present solidsupports. The solid support may optionally further comprise a pluralityof nucleic acid probes that hybridize to a plurality (e.g., two or more,or all) of the genes useful for the diagnosis of ischemic stroke,cardioembolic stroke, carotid stenosis, and/or atrial fibrillation, asdescribed herein. In various embodiments, the solid support comprises1000 or fewer (e.g., 900, 800, 700, 600, 500 or fewer) nucleic acidprobes that hybridize to a plurality of ischemia-associated genes, asdescribed herein. The solid support may be a component in a kit.

The invention also provides kits for diagnosing ischemia or apredisposition for developing ischemia. For example, the inventionprovides kits that include one or more reaction vessels that havealiquots of some or all of the reaction components of the invention inthem. Aliquots can be in liquid or dried form. Reaction vessels caninclude sample processing cartridges or other vessels that allow for thecontainment, processing and/or amplification of samples in the samevessel. The kits may comprise a plurality of nucleic acid probes thathybridize to a plurality (e.g., two or more, or all) of the genes setforth in Tables 3 and 4. In one embodiment, the kits comprise aplurality of nucleic acid probes that hybridize to a plurality of thegenes set forth in Table 3. In one embodiment, the kits comprise aplurality of nucleic acid probes that hybridize to a plurality of thegenes set forth in Table 4. In one embodiment, the kits further comprisea plurality of nucleic acid probes that hybridize to a plurality of thegenes set useful for the diagnosis of ischemic stroke, cardioembolicstroke, carotid stenosis, atrial fibrillation, and/or transient ischemicattacks (TIA), as described herein. The probes may be immobilized on anarray as described herein.

In addition, the kit can comprise appropriate buffers, salts and otherreagents to facilitate amplification and/or detection reactions (e.g.,primers, labels) for determining the expression levels of a plurality ofthe genes set forth in Tables 3 and 4. In one embodiment, the kitcomprises appropriate buffers, salts and other reagents to facilitateamplification and/or detection reactions (e.g., primers, labels) fordetermining the expression levels of a plurality of the genes set forthin Table 3. In one embodiment, the kit comprises appropriate buffers,salts and other reagents to facilitate amplification and/or detectionreactions (e.g., primers) for determining the expression levels of aplurality of the genes set forth in Table 4. In one embodiment, the kitfurther comprises appropriate buffers, salts and other reagents tofacilitate amplification and/or detection reactions (e.g., primers) fordetermining the expression levels of a plurality of the genes useful forthe diagnosis of ischemic stroke, cardioembolic stroke, carotidstenosis, atrial fibrillation, and/or transient ischemic attacks (TIA),as described herein. The kits can also include written instructions forthe use of the kit.

In one embodiment, the kits comprise a plurality of antibodies that bindto a plurality of the biomarkers set forth in Tables 3 and 4. The kitsmay further comprise a plurality of antibodies that bind to a pluralityof the biomarkers useful for the diagnosis of ischemic stroke,cardioembolic stroke, carotid stenosis, atrial fibrillation, and/ortransient ischemic attacks (TIA), as described herein. The antibodiesmay or may not be immobilized on a solid support, e.g., an ELISA plate.

EXAMPLES

The following examples are offered to illustrate, but not to limit theclaimed invention.

Example 1 Gene Expression Profiling to Distinguish Lacunar fromNon-Lacunar Stroke

Materials and Methods

Study Patients. Patients with SDI, strokes of arterial and cardioembolicetiology were enrolled from the University of California, Davis, and theUniversity of California, San Francisco. Study protocol was approved bythe institutional review board at each site and written informed consentwas obtained from each patient. Standardized clinical evaluations wereperformed on all patients including medical history, brain imaging,Doppler, vascular angiography, electrocardiogram, echocardiogram and24-48 hour cardiac monitoring. Blood samples were drawn into PAXgenetubes (PreAnalytiX, Hilden, Germany) within 72 hours of stroke onset forgene expression analysis.

The diagnosis of stroke was made by two board certified strokeneurologists. Lacunar stroke was defined by clinical symptoms consistentwith a lacunar syndrome and evidence of restricted diffusion on MRI witha largest diameter<15 mm occurring in the basal ganglia, thalamus,internal capsule, corona radiata or pons. Patients with lacunar strokedid not have evidence of embolic source despite investigation, includingno evidence of intracranial or extracranial stenosis>50% or a potentialmoderate to high risk cardioembolic source. Lacunar strokes withincomplete investigations were not included for study. SDI of unclearetiology were defined as infarction in the basal ganglia, thalamus,internal capsule, corona radiata or brainstem>15 mm in diameter or <15mm with a potential cardioembolic or ipsilateral arterial cause ofstroke. Non-lacunar strokes occurred had evidence of infarction onimaging non-lacunar stroke regions, and were of identified cardioembolicor arterial source. Cardioembolic strokes included patients with atrialfibrillation, acute myocardial infarction, valvular heart disease andmarked ventricular hypokinesis with hemispheric infarcts. Patients withPFO, atrial myxoma or endocarditis were not included. Arterial strokeswere defined as stenosis>50% of an extracranial or intracranial arteryreferable to the infarct without evidence of other cause of stroke.Differences between groups were analyzed using Fisher's exact test ortwo-tailed t-test where appropriate.

Sample Processing. PAXgene tubes were used to collect a venous bloodsample within 72 hours of stroke onset (PreAnalytiX, Germany). Sampleswere stored at −80° C. and processed at the same time in the samelaboratory to reduce batch effect. Total RNA was isolated according tothe manufacturer's protocol (PAXgene blood RNA kit; Pre-AnalytiX). RNAconcentration was determined by Nano-Drop (Thermo Fisher) and RNAquality by Agilent 2100 Bioanalyzer. Samples required A260/A280absorbance ratios of purified RNA≥2.0 and 28S/18S rRNA ratios≥1.8.Reverse transcription, amplification, and sample labeling were carriedout using NuGEN's Ovation Whole Blood Solution (NuGEN Technologies, SanCarlos, Calif.). Each RNA sample was hybridized according to themanufacturer's protocol on Affymetrix Human U133 Plus 2.0 GeneChips(Affymetrix Santa Clara, Calif.). Arrays were washed and processed on aFluidics Station 450 and scanned on a Genechip Scanner 3000. Sampleswere randomly assigned to microarray batch stratified by stroke subtype.

Data Analysis. Microarray data files were pre-processed using robustmultichip averaging (RMA), mean-centering standardization and log 2transformation. Partek Genomics Suite 6.4, Partek Inc., St. Louis, Mo.).Nonspecific interquartile range filtering was used to eliminateprobesets with low variation (<0.5) across the dataset (Hackstadt andHess, BMC Bioinformatics (2009) 10:11; Gentleman R., “Bioinformatics andcomputational biology solutions using R and Bioconductor,” in Statisticsfor biology and health. New York: Springer Science+Business Media; 2005.p. xix, 473 pp.). Of the original 54697 probesets, 21526 passed thisfiltering step and were retained for further analysis. Probesets werefurther selected by the differences in gene expression betweenphenotypic classes of interest using Analysis of Covariance (ANCOVA),adjusted for age and gender with a false discovery rate≤0.05 and foldchange≥|1.5| considered significant.

Classifier results were obtained using forward selection lineardiscriminant analysis with a multiple 10-fold cross-validation methodcomparing lacunar stroke to non-lacunar stroke. In each iteration, datawere divided into 10 equal-sized subsamples. Nine of the subsamples wereused to predict the cause of stroke in the remaining “left-out”subsample. This procedure was repeated 10 times, each time using adifferent left-out subsample, so that all patient samples were used toderive and evaluate predictors. Within each of the 10 folds of thecross-validation, the genes used in the classifier were reselected basedonly on the samples not left out, so that only the training set was usedto derive predictors for the left-out subsample. Selected predictorsrepresent genes whose expression is most stable within samples from thesame phenotypic class (e.g. lacunar stroke) and whose expression differsthe most between samples of a different class. Receiver operatingcharacteristics were derived based on the instance probability of classmembership and used to identify the optimal probability threshold toassign class membership to subjects of unknown stroke cause. The fullclassifier derived from subjects with known stroke subtype was furtherevaluated using a second validation cohort of subjects of known strokecause. To predict the stroke subtype in patients with SDI of unclearcause, the full classifier was applied to the gene expression values andclass membership assigned based on probability threshold determined fromthe training set. Logistic regression analyses were performed usingStata 10.1 (College Station, Tex., USA). Variables on univariateanalysis with p≤0.2 were included in multivariate analysis. Results arereported as odds ratios (OR) with 95% confidence intervals.

Ingenuity Pathway Analysis (IPA, Ingenuity Systems®, on the internet atingenuity.com) was used to identify the functional pathways associatedwith the 90 genes. This was done by testing whether the number of genesin a given pathway was greater than that expected by chance (p<0.05considered significant using a Fisher's exact test).

Results

There were 116 subjects with ischemic stroke in the training cohort forthis study. The mean age was 67 years (SD 10.7) and 54% were male. Thecohort was ethnically mixed: 72 (62%) were Caucasian, 22 (19%) wereAfrican American, 7 (6%) were Hispanic, 7 (6%) were Asian, and 8 (7%) ofother race. Demographic and clinical characteristics of subjects used inthe training group for the comparison of lacunar stroke to non-lacunarstroke are shown in Table 2. There were 30 samples with lacunar strokeand 86 subjects with non-lacunar stroke (56 cardioembolic stroke, 30arterial stroke). Age, NIHSS on admission, race, arterial source andcardiac source were significantly different between lacunar stroke andnon-lacunar stroke patients (p<0.05).

TABLE 2 Demographic variables for patients with lacunar and non-lacunarischemic stroke Lacunar Non-Lacunar (n = 30) (n = 86) p-value Age years(SD) 61.1 (12.7) 69.1 (12.7) <0.001 Race Caucasian n (%) 12 (40.0%) 60(69.8%) 0.005 Gender Male n (%) 13 (43.3%) 55 (63.9%) 0.056Adm-Temperature ° C. (SD) 36.3 (0.5) 36.4 (0.1) 0.616 Adm-NIHSS (SD) 2.2(2.9) 10.2 (9.3) <0.001 Hypertension n (%) 24 (80.0%) 61 (70.9%) 0.473Systolic BP mmHg (SD) 163.2 (32.8) 157.4 (28.2) 0.358 Diastolic BP mmHg(SD) 87.6 (20.3) 82.0 (18.1) 0.156 Diabetes n(%) 13 (43.3%) 24 (27.9%)0.171 Weight kg (SD) 79.4 (22.7) 88.5 (19.8) 0.376 Hyperlipidemia n (%)13 (43.3%) 40 (46.5%) 0.647 Atrial fibrillation n (%) 0 (0%) 25 (29.1%)<0.001 Cardiac Source 0 (0%) 56 (65.1%) <0.001 Arterial Source 0 (0%) 30(34.9%) <0.001 Prior Stroke/TIA n (%) 5 (16.7%) 21 (24.4%) 0.454 PriorMI n (%) 2 (6.7%) 16 (18.6%) 0.151 CAGB n (%) 1 (3.3%) 14 (16.3%) 0.111Abbreviations: Adm, admission; BP, blood pressure; CABG, coronary arterybypass graft; MI, myocardial infarction; NIHSS, National Institutes ofHealth Stroke Scale.

A total of 96 probesets representing 90 genes were significantlydifferent between lacunar and non-lacunar strokes (FDR<0.05 foldchange>|1.5|) (Table 3). The 96 probesets were reduced to a list of 41probesets (40 genes) using forward selection linear discriminantanalysis (Table 4). A cluster plot and a plot of fold change for the 41probesets that distinguish lacunar versus non-lacunar strokes are shownin FIG. 1. Detailed box plots of the mean centered expression values areshown in FIG. 2. A linear discriminant analysis model of the 41probesets correctly distinguished lacunar from non-lacunar stroke in 97%of patients. Receiver Operating Characteristics curve was used toidentify 0.7 as the optimal instance probability to discriminate betweenlacunar and non-lacunar stroke (true positive rate 0.97, false positiverate 0) (FIG. 3). Ten-fold cross-validation analysis was performed toevaluate prediction in the training set. The 41 probesets distinguishedlacunar from non-lacunar stroke in 88% of patients (22/30 lacunarstrokes; 80/86 non-lacunar strokes) (FIG. 4).

TABLE 3 96 Probesets Representing 90 Genes Significantly DifferentBetween Lacunar and Non-Lacunar Strokes p-value Fold-Change (Lacunar vs.(Lacunar vs. Probeset ID Gene Symbol Gene Title RefSeq Transcript IDNon-Lacune) Non-Lacune) 218091_at AGFG1 ArfGAP with FG repeats 1NM_001135187 /// 0.00235784 −1.50067 NM_001135188 /// NM_001135189 ///NM_004504 215483_at AKAP9 A kinase (PRKA) anchor protein (yotiao) 9NM_005751 /// 0.00971715 1.57928 NM_147185 1553261_x_at ALS2CR11amyotrophic lateral sclerosis 2 (juvenile) chromosome NM_1525250.00536689 1.59132 region, candidate 11 235723_at BNC2 basonuclin 2NM_017637 0.00937559 1.56652 1559975_at BTG1 B-cell translocation gene1, anti-proliferative NM_001731 0.00376377 −1.53002 205839_s_at BZRAP1benzodiazapine receptor (peripheral) associated protein 1 NM_004758 ///0.006889 1.53193 NM_024418 232222_at C18orf49 chromosome 18 open readingframe 49 — 0.00266419 1.55196 213688_at CALM1 calmodulin 1(phosphorylase kinase, delta) NM_006888 0.00235943 1.61152 233157_x_atCCDC114 coiled-coil domain containing 114 NM_144577 0.00154458 1.65214236745_at CCDC78 coiled-coil domain containing 78 NM_0010317370.00537949 1.5279 216598_s_at CCL2 chemokine (C-C motif) ligand 2NM_002982 0.00400012 1.5258 205114_s_at CCL3 /// chemokine (C-C motif)ligand 3 /// NM_001001437 /// 0.00302906 1.51515 CCL3L1 /// chemokine(C-C motif) ligand 3-like 1 /// NM_002983 /// CCL3L3 chemokine (C-Cmotif) ligand 3-like 3 NM_021006 204103_at CCL4 chemokine (C-C motif)ligand 4 NM_002984 0.00624874 1.54555 236588_at CFDP1 Craniofacialdevelopment protein 1 NM_006324 0.00526084 −1.53983 206079_at CHMLchoroideremia-like (Rab escort protein 2) NM_001821 9.68E−05 −1.83008203921_at CHST2 carbohydrate (N-acetylglucosamine-6-O) sulfotransferase2 NM_004267 0.00531986 1.581 1557798_at CNPY2 Canopy 2 homolog(zebrafish) NM_014255 0.00452098 −1.52001 209716_at CSF1 colonystimulating factor 1 (macrophage) NM_000757 /// 0.000674827 1.7117NM_172210 /// NM_172211 /// NM_172212 216836_s_at ERBB2 v-erb-b2erythroblastic leukemia viral oncogene homolog 2, NM_001005862 ///0.00462673 1.62126 neuro/glioblastoma de NM_004448 219694_at FAM105Afamily with sequence similarity 105, member A NM_019018 0.00379549−1.50378 236717_at FAM179A family with sequence similarity 179, member ANM_199280 0.00311876 1.6413 238226_at FAM70B family with sequencesimilarity 70, member B NM_182614 0.00173252 −1.51382 1559011_atFLJ13773 FLJ13773 — 0.000601925 −1.76819 203178_at GATM glycineamidinotransferase (L-arginine:glycine NM_001482 0.00359043 −1.5849amidinotransferase) 235175_at GBP4 guanylate binding protein 4 NM_0529410.00445442 1.53211 235574_at GBP4 guanylate binding protein 4 NM_0529410.00465219 1.50933 212070_at GPR56 G protein-coupled receptor 56NM_001145770 /// 0.00399735 1.61 NM_001145771 /// NM_001145772 ///NM_001145773 /// NM_001145774 238049_at GRAMD3 GRAM domain containing 3NM_001146319 /// 0.00914244 1.5714 NM_001146320 /// NM_001146321 ///NM_001146322 /// NM_023927 219388_at GRHL2 grainyhead-like 2(Drosophila) NM_024915 0.00901445 1.59441 208365_s_at GRK4 Gprotein-coupled receptor kinase 4 NM_001004056 /// 0.00677744 1.54491NM_001004057 /// NM_182982 223758_s_at GTF2H2 general transcriptionfactor IIH, polypeptide 2, 44 kDa NM_001515 0.00136485 −1.70078221540_x_at GTF2H2 /// general transcription factor IIH, polypeptide 2,NM_001042490 /// 0.00365515 −1.55919 GTF2H2B /// 44 kDa /// generaltranscription NM_001098728 /// GTF2H2C /// NM_001098729 /// GTF2H2DNM_001515 203290_at HLA-DQA1 major histocompatibility complex, class II,DQ alpha 1 NM_002122 2.54E−08 −2.20603 209728_at HLA-DRB4 majorhistocompatibility complex, class II, DR beta 4 NM_021983 /// 6.99E−061.91608 XM_002346251 216318_at IGHG1 Immunoglobulin heavy constant gamma1 (G1m marker) — 0.00296031 −1.6144 207072_at IL18RAP interleukin 18receptor accessory protein NM_003853 0.00151018 −1.52093 211506_s_at IL8interleukin 8 NM_000584 0.00463242 −1.50845 242720_at ITIH4 inter-alpha(globulin) inhibitor H4 (plasma Kallikrein- NM_002218 0.00592498 1.56018sensitive glycoprotein) 241347_at KIAA1618 KIAA1618 NM_020954 0.001639721.59688 206486_at LAG3 lymphocyte-activation gene 3 NM_002286 0.008154931.51228 207509_s_at LAIR2 leukocyte-associated immunoglobulin-likereceptor 2 NM_002288 /// 0.00045044 1.81862 NM_021270 227819_at LGR6leucine-rich repeat-containing G protein-coupled receptor 6 NM_001017403/// 0.000192318 1.80854 NM_001017404 /// NM_021636 227835_atLOC100132181 Hypothetical protein LOC100132181 — 0.000335926 1.759131560830_a_at LOC147646 hypothetical protein LOC147646 XM_001134195 ///0.000324794 1.60942 XM_001134326 /// XM_001726058 236739_at LOC150622hypothetical LOC150622 NR_026832 0.0077732 1.60267 211012_s_at LOC161527/// hypothetical protein LOC161527 NM_002675 /// 0.0032518 1.54307 PML/// NM_033238 /// promyelocytic leukemia NM_033239 /// NM_033240 ///NM_033244 /// NM_033246 1557059_at LOC254128 Hypothetical proteinLOC254128 — 0.00124615 −1.62167 212978_at LRRC8B leucine rich repeatcontaining 8 family, member B NM_001134476 /// 0.00102493 −1.65702NM_015350 1570585_at MPZL3 myelin protein zero-like 3 NM_1982750.000173204 −1.60248 231996_at N4BP2 NEDD4 binding protein 2 NM_0181770.00206464 −1.58061 205660_at OASL 2′-5′-oligoadenylate synthetase-likeNM_003733 /// 0.000308002 1.63843 NM_198213 210797_s_at OASL2′-5′-oligoadenylate synthetase-like NM_003733 /// 0.000396146 1.62541NM_198213 1555347_at PDXDC1 pyridoxal-dependent decarboxylase domaincontaining 1 NM_015027 0.000777978 −1.56922 232045_at PHACTR1phosphatase and actin regulator 1 NM_030948 0.00329088 −1.59346219566_at PLEKHF1 pleckstrin homology domain containing, family FNM_024310 0.000614903 1.75195 (with FYVE domain) member 1 209282_atPRKD2 protein kinase D2 NM_001079880 /// 0.00358506 1.60351 NM_001079881/// NM_001079882 /// NM_016457 203650_at PROCR protein C receptor,endothelial (EPCR) NM_006404 0.00566754 1.56281 229441_at PRSS23Protease, serine, 23 NM_007173 0.00146505 1.69157 212262_at QKI quakinghomolog, KH domain RNA binding (mouse) NM_006775 /// 0.00955483 −1.53363NM_206853 /// NM_206854 /// NM_206855 1553185_at RASEF RAS and EF-handdomain containing NM_152573 0.00304521 1.68262 1553186_x_at RASEF RASand EF-hand domain containing NM_152573 0.00504528 1.65073 1554003_atRGNEF Rho-guanine nucleotide exchange factor NM_001080479 0.004421021.50745 230469_at RTKN2 rhotekin 2 NM_145307 0.00997383 −1.51471204197_s_at RUNX3 runt-related transcription factor 3 NM_001031680 ///0.00898405 1.51341 NM_004350 206021_at SCAND2 SCAN domain containing 2pseudogene NR_003654 /// 0.00891229 1.5413 NR_004859 223196_s_at SESN2sestrin 2 NM_031459 0.0054103 1.54604 222838_at SLAMF7 SLAM familymember 7 NM_021181 0.00335692 1.56069 202234_s_at SLC16A1 solute carrierfamily 16, member 1 (monocarboxylic acid NM_003051 0.00459743 −1.60487transporter 1) 210001_s_at SOCS1 suppressor of cytokine signaling 1NM_003745 0.00463398 −1.51277 233516_s_at SPAG17 sperm associatedantigen 17 NM_206996 0.00242632 −1.5873 218638_s_at SPON2 spondin 2,extracellular matrix protein NM_001128325 /// 0.00363533 1.59641NM_012445 227725_at ST6GALNAC1 ST6(alpha-N-acetyl-neuraminyl-2,3-beta-galactosyl- NM_018414 0.00587704−1.54288 1,3)-N-acetylgalactosaminide AFFX- STAT1 signal transducer andactivator of transcription 1, 91 kDa NM_007315 /// 0.0096253 1.53095HUMISGF3A/ NM_139266 M97935_MA_at 243797_at STK17B serine/threoninekinase 17b NM_004226 0.0015488 −1.59518 1569791_at STK4 serine/threoninekinase 4 NM_006282 0.00872568 −1.53645 231294_at STT3B STT3, subunit ofthe oligosaccharyltransferase complex, NM_178862 0.00659319 −1.55741homolog B (S. cerevisiae 221499_s_at STX16 syntaxin 16 NM_001001433 ///0.00402852 −1.5285 NM_001134772 /// NM_001134773 /// NM_003763 212631_atSTX7 syntaxin 7 NM_003569 0.00132752 −1.60106 210613_s_at SYNGR1synaptogyrin 1 NM_004711 /// 0.00217283 1.51053 NM_145731 /// NM_1457381557609_s_at TBC1D12 TBC1 domain family, member 12 NM_015188 0.00719049−1.54224 220684_at TBX21 T-box 21 NM_013351 0.00748882 1.53529 204731_atTGFBR3 transforming growth factor, beta receptor III NM_0032430.00132619 1.68066 1569377_at TMEM67 transmembrane protein 67NM_001142301 /// 0.00862787 1.52234 NM_153704 /// NR_024522 223384_s_atTRIM4 tripartite motif-containing 4 NM_033017 /// 0.00353022 −1.56529NM_033091 225879_at TSEN54 tRNA splicing endonuclease 54 homolog (S.cerevisiae) NM_207346 0.00299112 1.52859 219587_at TTC12tetratricopeptide repeat domain 12 NM_017868 0.00822832 1.53053230891_at TUBE1 Tubulin, epsilon 1 NM_016262 0.00822258 1.57063223279_s_at UACA uveal autoantigen with coiled-coil domains and ankyrinNM_001008224 /// 0.00474228 −1.55924 repeats NM_018003 203281_s_at UBA7ubiquitin-like modifier activating enzyme 7 NM_003335 0.00155438 1.56379221765_at UGCG UDP-glucose ceramide glucosyltransferase NM_0033580.00265623 −1.61812 224967_at UGCG UDP-glucose ceramideglucosyltransferase NM_003358 0.00349479 −1.53463 220784_s_at UTS2urotensin 2 NM_006786 /// 6.48E−05 1.73209 NM_021995 220785_at UTS2urotensin 2 NM_006786 /// 0.000281237 1.55721 NM_021995 242780_at VAPAVAMP (vesicle-associated membrane protein)-associated NM_003574 ///0.00827971 −1.54802 protein A, 33 kDa NM_194434 1557450_s_at WHAMML2 WASprotein homolog associated with actin, golgi NR_026589 0.00204599−1.61055 membranes and microtubules-like 243618_s_at ZNF827 Zinc fingerprotein 827 NM_178835 0.00743837 1.60401

TABLE 4 41 Probesets Using Forward Selection Linear DiscriminantAnalysis p-value Fold-Change RefSeq (Lacunar vs. (Lacunar vs. ProbesetID Gene Symbol Gene Title Transcript ID Non-Lacune) Non-Lacune)1553261_x_at ALS2CR11 amyotrophic lateral sclerosis 2 (juvenile)chromosome NM_152525 0.00536689 1.59132 region, candidate 11 232222_atC18orf49 chromosome 18 open reading frame 49 — 0.00266419 1.55196213688_at CALM1 calmodulin 1 (phosphorylase kinase, delta) NM_0068880.00235943 1.61152 233157_x_at CCDC114 coiled-coil domain containing 114NM_144577 0.00154458 1.65214 236745_at CCDC78 coiled-coil domaincontaining 78 NM_001031737 0.00537949 1.5279 216598_s_at CCL2 chemokine(C-C motif) ligand 2 NM_002982 0.00400012 1.5258 205114_s_at CCL3 ///chemokine (C-C motif) ligand 3 /// NM_001001437 /// 0.00302906 1.51515CCL3L1 /// chemokine (C-C motif) ligand 3-like 1 /// NM_002983 ///CCL3L3 chemokine (C-C motif) ligand 3-like 3 NM_021006 206079_at CHMLchoroideremia-like (Rab escort protein 2) NM_001821 9.68E−05 −1.83008236717_at FAM179A family with sequence similarity 179, member ANM_199280 0.00311876 1.6413 238226_at FAM70B family with sequencesimilarity 70, member B NM_182614 0.00173252 −1.51382 1559011_atFLJ13773 FLJ13773 — 0.000601925 −1.76819 235175_at GBP4 guanylatebinding protein 4 NM_052941 0.00445442 1.53211 223758_s_at GTF2H2general transcription factor IIH, polypeptide 2, 44 kDa NM_0015150.00136485 −1.70078 203290_at HLA-DQA1 major histocompatibility complex,class II, DQ alpha 1 NM_002122 2.54E−08 −2.20603 209728_at HLA-DRB4major histocompatibility complex, class II, DR beta 4 NM_021983 ///6.99E−06 1.91608 XM_002346251 211506_s_at IL8 interleukin 8 NM_0005840.00463242 −1.50845 206486_at LAG3 lymphocyte-activation gene 3NM_002286 0.00815493 1.51228 207509_s_at LAIR2 leukocyte-associatedimmunoglobulin-like receptor 2 NM_002288 /// 0.00045044 1.81862NM_021270 227819_at LGR6 leucine-rich repeat-containing Gprotein-coupled NM_001017403 /// 0.000192318 1.80854 receptor 6NM_001017404 /// NM_021636 227835_at LOC100132181 Hypothetical proteinLOC100132181 — 0.000335926 1.75913 1557059_at LOC254128 Hypotheticalprotein LOC254128 — 0.00124615 −1.62167 212978_at LRRC8B leucine richrepeat containing 8 family, member B NM_001134476 /// 0.00102493−1.65702 NM_015350 1570585_at MPZL3 myelin protein zero-like 3 NM_1982750.000173204 −1.60248 205660_at OASL 2′-5′-oligoadenylate synthetase-likeNM_003733 /// 0.000308002 1.63843 NM_198213 1555347_at PDXDC1pyridoxal-dependent decarboxylase domain containing 1 NM_0150270.000777978 −1.56922 203650_at PROCR protein C receptor, endothelial(EPCR) NM_006404 0.00566754 1.56281 229441_at PRSS23 Protease, serine,23 NM_007173 0.00146505 1.69157 212262_at QKI quaking homolog, KH domainRNA binding (mouse) NM_006775 /// 0.00955483 −1.53363 NM_206853 ///NM_206854 /// NM_206855 1553185_at RASEF RAS and EF-hand domaincontaining NM_152573 0.00304521 1.68262 204197_s_at RUNX3 runt-relatedtranscription factor 3 NM_001031680 /// 0.00898405 1.51341 NM_004350206021_at SCAND2 SCAN domain containing 2 pseudogene NR_003654 ///0.00891229 1.5413 NR_004859 1569791_at STK4 serine/threonine kinase 4NM_006282 0.00872568 −1.53645 212631_at STX7 syntaxin 7 NM_0035690.00132752 −1.60106 204731_at TGFBR3 transforming growth factor, betareceptor III NM_003243 0.00132619 1.68066 225879_at TSEN54 tRNA splicingendonuclease 54 homolog (S. cerevisiae) NM_207346 0.00299112 1.52859219587_at TTC12 tetratricopeptide repeat domain 12 NM_017868 0.008228321.53053 203281_s_at UBA7 ubiquitin-like modifier activating enzyme 7NM_003335 0.00155438 1.56379 221765_at UGCG UDP-glucose ceramideglucosyltransferase NM_003358 0.00265623 −1.61812 220784_s_at UTS2urotensin 2 NM_006786 /// 6.48E−05 1.73209 NM_021995 220785_at UTS2urotensin 2 NM_006786 /// 0.000281237 1.55721 NM_021995 242780_at VAPAVAMP (vesicle-associated membrane protein)- NM_003574 /// 0.00827971−1.54802 associated protein A, 33 kDa NM_194434

The model derived from the training cohort was applied to a secondvalidation test cohort of 36 ischemic stroke subjects of knownnon-lacunar etiology. The 41 probesets were able to correctly classify35 of the 36 (98%) strokes as non-lacunar.

The model was applied to subjects with SDI of unclear cause (SDI>15 mmand SDI with possible embolic source). Of the 32 SDI patients, 15 werepredicted to be of lacunar etiology and 17 were predicted to be ofnon-lacunar etiology. To identify clinical features associated with theSDI of predicted lacunar etiology, univariate analysis was performed.SDI predicted to be lacunar were less likely to be of Caucasianrace/ethnicity (OR 0.18, 0.04-0.86), less likely to have potentialarterial source of stroke (OR 0.2, 0.04-0.9) and trended to have fewerpotential cardiac source of stroke (OR 0.28, 0.04-1.69) (Table 5). Thepresence of hypertension and diabetes were not significantly increasedin SDI predicted to be lacunar.

TABLE 5 Univariate logistic regression analysis of small deep infarcts(SDI) predicted to be lacunar (n = 15) compared to SDI predicted to benon-lacunar (n = 17) 95% Conf Odds Ratio Interval p-value Age years 0.970.91-1.02 0.257 Race Caucasian 0.18 0.04-0.86 0.032 Gender Male 0.820.20-3.43 0.784 Adm-Temperature ° C. 0.99 0.97-1.03 0.960 Adm-NIHSS 0.920.71-1.19 0.522 Hypertension 0.87 0.11-7.04 0.894 Systolic BP mmHg 0.990.98-1.01 0.725 Diastolic BP mmHg 1.01 0.97-1.05 0.674 Diabetes 0.950.23-3.92 0.946 Weight kg 0.98 0.94-1.03 0.393 Hyperlipdemia 0.280.06-1.21 0.087 Prior Stroke/TIA 0.87 0.19-4.11 0.863 Infarct Diameter1.06 0.98-1.15 0.122 Striatocapsular location 3.00 0.67-13.3 0.148 ARWMCScore 0.97 0.87-1.08 0.574 Microhemorrhage 0.20 0.02-2.02 0.171 Arterialsource (ipsilateral) 0.20 0.04-0.90 0.037 Cardiac source 0.28 0.04-1.690.166 Atrial Fibrillation 0.33 0.03-3.61 0.366 Abbreviations: Adm,admission; ARWMC, Age Related White Matter Changes; BP, blood pressure;MI, myocardial infarction; NIHSS, National Institutes of Health StrokeScale.

Multivariate logistic regression was performed to identify independentpredictors of lacunar infarction. Independent predictors of SDI being oflacunar etiology were non-Caucasian race (OR 0.06, 0.005-0.60) and theabsence arterial disease ipsilateral to the stroke (OR 0.06,0.006-0.64). Table 6 shows the results of a multivariate stepwiselogistic regression of all variables with p<0.2 on univariate analysisto identify independent predictors of lacunar stroke in small deepinfarcts of unclear cause. Variables included in the model were arterialsource, cardiac source, race Caucasian, striatocapsular location,infarct size, microhemorrhage and hyperlipidemia.

TABLE 6 95% Conf OR Interval p-value Arterial source 0.056 0.006-0.640.019 (ipsilateral) Race Caucasian 0.063 0.005-0.60 0.017

Functional analysis of the 96 probesets revealed several pathways thatwere represented greater than expected by chance. The majority ofpathways represented alterations in immune cells in the blood ofpatients with lacunar stroke. The top ten functional and canonicalpathways are listed in Table 7, along with the genes expressed in thesepathways. Table 7 shows a functional analysis of the 96 probesets (90genes) that were different between lacunar and non-lacunar stroke. Thetop functional and canonical pathways that were represented greater thanexpected by chance (p<0.05, Fisher's exact test), along with the genesexpressed in the listed pathways. The majority of pathways representalterations in immune cells in the blood of patients with lacunar strokethat are different from non-lacunar stroke patients.

TABLE 7 Pathway Genes p-value Canonical Innate and Adaptive Immune CellCCL3, CCL4, HLA-DRB4, IGHA1, 4.8 × 10⁻⁵ Pathways Communication IL8 TREM1Signaling CCL2, CCL3, IL8 3.2 × 10⁻³ T Helper Cell DifferentiationHLA-DQA1, STAT1, TBX21 4.9 × 10⁻³ CCR5 Signaling in Macrophages CALM1,CCL3, CCL4 5.6 × 10⁻³ Role Macrophages, Fibroblasts and CALM1, CCL2,CSF1, IL8, 6.6 × 10⁻³ Endothelial Cells in Rheumatoid Arthritis IL18RAP,SOCS1 Chemokine Signaling CALM1, CCL2, CCL4 6.9 × 10⁻³ InterferonSignaling SOCS1, STAT1 1.3 × 10⁻² IL-6 Signaling IL8, IL18RAP, SOCS1 1.5× 10⁻² Antigen Presentation Pathways HLA-DQA1, HLA-DRB4 1.5 × 10⁻²Molecular Growth of Myeloid Cells & Leukocytes CCL2, CCL3, CSF1, ERBB2,IL8, 3.6 × 10⁻⁹ Functions LAG3, PML, SOCS1 Monocyte & LeukocyteActivation and CCL2, CCL3, CCL4, CSF1, HLA- 1.9 × 10⁻⁶ Recruitment DQA1,IL8, RUNX3, SPON2, STAT1, UTS2 Immune Response CCL2, CCL3, CCL4, CSF1,ERBB2, 2.2 × 10⁻⁵ HLA-DQA1, HLA-DRB4, IL8, IL18RAP, LAG3, SOCS1, SPON2,STAT1, STK17B, TBX21, TGFBR3 Cardiovascular process of blood vessel,BTG1, CCL2, CCL3, IL8, PML, 9.5 × 10⁻⁴ endothelial adhesion RUNX3, STK4,STX7, TGFBR3, UTS2 Angiogenesis of endothelial cells ERBB2, IL8 2.2 ×10⁻³

To validate the method of gene selection and prediction modeldevelopment, the entire process was repeated with gender as the outcomevariable to be predicted. A profile of 41 distinct genes was derived inthe training cohort that was significantly different between males andfemales (FDR≤0.05, fold change>|1.5|). A linear discriminant analysismodel, built using these 41 genes, correctly predicted gender in allpatients (86+30=116 out of 116 correct) on cross-validation analysis.The model was also evaluated on the validation set of 36 embolicsubjects and the 30 SDI subjects, correctly predicting gender in allsubjects (36/36 and 30/30). This shows that the methods used to deriveand evaluate the outcome measure of lacunar stroke worked well and asexpected.

Discussion

The present study demonstrates that a gene expression profile can beused to distinguish patients with lacunar stroke from non-lacunarstroke. Further, when this gene expression profile is applied topatients with SDI of unclear cause (SDI>15 mm and SDI<15 mm withpotential embolic sources), both lacunar and non-lacunar causes can bepredicted. Clinical features associated with SDI of predicted lacunaretiology were non-Caucasian race and lack of arterial source. Given thedifficulty in distinguishing lacunar from non-lacunar causes of SDI andthe importance of this distinction in clinical management, developing areliable expression profile for predicting or determining lacunaretiology finds clinical use.

Arterial Small Deep Infarcts

The presence of arterial disease ipsilateral to an SDI has beensuggested as an indicator of non-lacunar infarction (Cupini, et al.,Stroke (2002) 33(3):689-94; and Silvestrini, et al., J Neurol. (2006)253(3):321-7). Patients with carotid or vertebral stenosis>50%ipsilateral to an SDI are often classified as a non-lacunar infarction.However, whether the arterial disease is the actual cause of the SDI ora coincidental disease occurring in a patient with symptomatic smallvessel disease remains unclear (Devuyst and Bogousslavsky, Stroke (2003)34(6): 1409-11). Symptomatic carotid stenosis derives greater benefitfrom vascular intervention. Thus ascertaining whether the SDI is oflacunar or arterial etiology is of clinical significance. Furthermore,correct classification of stroke cause is important for clinicalresearch of disease mechanism and the development of therapeutics.

Carotid endarterectomy in SDI patients with carotid stenosis doesimprove outcomes, supporting the argument that arterial disease is acause of some SDI (Halliday, et al., Lancet (2010) 376(9746):1074-84;Lindley, et al., Lancet Neurol. (2009) 8(7):628-34). However, thebenefit of endarterectomy in patients with SDI is less than for otherstroke subtypes, potentially indicating that only a portion of SDI withcarotid stenosis are truly symptomatic (Lindley, et al., supra). Otherstudies also suggest that arterial disease causes some SDI, with degreeof vascular stenosis, intima medial thickness and arterial stiffness allhaving been reported as predictors of non-lacunar stroke (Jackson andSudlow, Brain (2005) 128(Pt 11):2507-17; Lee, et al., Stroke (2005)36(12):2583-8; Cupini, et al., Stroke (2002) 33(3):689-94; Silvestrini,et al., J Neurol. (2006) 253(3):321-7; Tuttolomondo, et al.,Atherosclerosis (2010) 211(1): 187-94; Jackson, et al. Stroke (2010)41(4):624-9; Nah, et al., Stroke (2010) 41(12):2822-7; Cho, et al., EurNeurol. (2010) 63(2): 107-15; Mead, et al., J Neurol NeurosurgPsychiatry (1999) 67(5):682-4; Baumgartner, et al., Stroke (2003)34(3):653-9; Bang, et al., Arch Neurol. (2004) 61(4):514-9; Kim, et al.,Eur Neurol. (2010) 63(6):343-9; Bang, et al., Arch Neurol. (2002)59(2):259-63). Additionally, Tejada, et al. reported a 7% absoluteincrease in ipsilateral compared to contralateral carotid stenosis inpatients with SDI, suggesting carotid disease contributes to some SDI(Tejada, et al., Stroke (2003) 34(6):1404-9). However, this finding hasnot been demonstrated by others (Mead, et al., J Neurol. (2002)249(3):266-71). Our study supports the notion that the presence ofarterial disease is associated with non-lacunar infarction. Among the 32patients with SDI of unclear cause, those predicted to have non-lacunarinfarction were over five times more likely to have ipsilateral arterialdisease.

Not all SDI with arterial disease were predicted to be of non-lacunaretiology. In 4 out of 12 SDI with arterial disease, a lacunar etiologywas predicted. This suggests that some patients with SDI haveasymptomatic arterial disease, coincidental to infarction. There were noclinical features recorded that were significantly different between SDIwith arterial disease of predicted lacunar etiology compared to those ofpredicted non-lacunar etiology.

Cardioembolic Small Deep Infarcts

The presence of a cardiac source has also been suggested as a marker ofnon-lacunar SDI (Arboix, et al., BMC Neurol. (2010) 10:31; Jackson, etal. Stroke (2010) 41(4):624-9; Mead, et al., J Neurol NeurosurgPsychiatry (1999) 67(5):682-4; Jackson and Sudlow, Stroke (2005)36(4):891-901; Bejot, et al., Stroke (2008) 39(7):1945-51; Lodder, etal., Stroke (1990) 21(3):375-81; Micheli, et al., J Neurol. (2008)255(5):637-42; Jung, et al., J Neurol Neurosurg Psychiatry. (2001)70(3):344-9; and Gouw, et al., Stroke (2008) 39(11):3083-5). In thepresent study, there was a trend for a cardiac source to be more commonin SDI predicted to be of non-lacunar etiology, though statisticallysignificant was not achieved. There were two subjects predicted to havelacunar stroke, one with atrial fibrillation and the other withcardiomyopathy. This suggests that some cardiac sources are coincidentalto SDI, and some are probably causal. No clinical features wereidentified to be significantly different between SDI with a potentialcardiac source of predicted lacunar versus non-lacunar etiology, thoughsample size was small.

Vascular Risk Factors, Race and Small Deep Infarcts

Vascular risk factor profiles are similar between lacunar andnon-lacunar stroke (Jackson, et al. Stroke (2010) 41(4):624-9; Jacksonand Sudlow, Stroke (2005) 36(4):891-901; Jackson and Sudlow, Brain(2005) 128(Pt 11):2507-17; and Bejot, et al., Stroke (2008)39(7):1945-51). This is consistent with our study which did not identifyhypertension or diabetes as being associated with a predicted diagnosisof lacunar infarction. However, non-Caucasian race/ethnicity wasidentified as being more common in SDI predicted to be of lacunaretiology. It is suggested that lacunar stroke occurs more frequently innon-Caucasians, including African American, Asian and Latino (Gross, etal., Stroke (1984) 15(2):249-55; Bamford, et al., Stroke (1987)18(3):545-51; Bogousslavsky, et al., Stroke (1988) 19(9):1083-92; Huang,et al., Stroke (1990) 21(2):230-5, and Ohira, et al., Stroke (2006)37(10):2493-8). Interestingly, non-Caucasian strokes also tend to havemore intracranial atherosclerotic disease (Sacco, et al., Stroke (1997)28(5):929-35; Sacco, Stroke (1995) 26(1):14-20; Gorelick, Stroke (1993)24(12 Suppl):I16-9; discussion I20-1; Caplan, et al., Stroke (1986)17(4):648-55). Whether race is an indicator of intracranial vasculardisease not detected by angiography that is associated with lacunarstroke is an interesting possibility.

Lacunar Small Deep Infarcts

The diagnosis of lacunar stroke was made using clinical symptoms,imaging and ancillary investigation rule out other potential etiologies.Such features have been shown to make lacunar small vessel disease themost likely cause of a small deep infarct. This is indeed true in ourstudy, where 22 out of 30 lacunar strokes were classified as lacunar oncross-validation analysis. However, there were 8 patients who met thecriteria for lacunar stroke who were predicted to have a non-lacunaretiology based on their pattern of gene expression. Of interest none ofthese 8 patients had evidence of microhemorrhage on gradient echo recallMRI, whereas 6 of the 22 lacunar strokes of predicted lacunar etiologydid (p=0.09). Though sample size in our study was small, the suggestionthat microhemorrhages may be an important marker of lacunar stroke haspreviously been reported (Wardlaw, et al., Stroke (2006) 37(10):2633-6;Fan, et al., J Neurol. (2004) 251(5):537-41, Schonewille, et al., JStroke Cerebrovasc Dis. (2005) 14(4): 141-4). In future studies, moredetailed analysis of small vessel disease markers includingmicrohemorrhage, retinal imaging, blood brain barrier permeability andblood endothelial markers may provide better insight into featurescharacteristic of lacunar stroke.

The identified differences in blood reflect immune differences betweenlacunar and embolic stroke, including differences in immune response tovascular risk factors. The genes identified as differentially expressedin lacunar stroke were over represented in canonical pathways involvinginnate and adaptive immune cell communication, TREM1 signaling, T-helpercell differentiation and immune cell signaling (Table 7). Overrepresented functional pathways included growth, activation andrecruitment of leukocytes and myeloid cells, endothelial adhesion andangiogenesis. Specific inflammatory and/or genetic factors maypredispose to endothelial damage. Indeed, others have identified markersof inflammation and endothelial dysfunction to be associated withlacunar strokes (Hassan, et al., Brain (2003) 126(Pt 2):424-32; vanIterson, et al., BMC Bioinformatics (2010) 11:450; Bevan, et al., Stroke(2008) 39(4):1109-14).

The present invention demonstrates that prediction of small deepinfarcts of both lacunar and non-lacunar etiology. Further work-up ofpatients with SDI infarction can be performed to identify potentialcardioembolic and arterial causes. Though clinical and imaging featuresmay distinguish most lacunar strokes, there remains a group of SDI withnon-lacunar etiologies that may require different management. Geneexpression analysis shows promise as a powerful method to infer SDIetiology.

It is understood that the examples and embodiments described herein arefor illustrative purposes only and that various modifications or changesin light thereof will be suggested to persons skilled in the art and areto be included within the spirit and purview of this application andscope of the appended claims. All publications, sequences of accessionnumbers, patents, and patent applications cited herein are herebyincorporated by reference in their entirety for all purposes.

What is claimed is:
 1. A solid support comprising a plurality of nucleicacid probes that specifically hybridize to a plurality of lacunarstroke-associated genes comprising HLA-DQA1, FLJ13773, RASEF, CALM1,QKI, TTC12, CCL3, CCL3L1, CCL3L3, CCDC78, PRSS23, LAIR2, C18orf49,MPZL3, UTS2, FAM70B, UTS2, LOC254128, LGR6, IL8, CHML, STX7, PROCR,VAPA, LAG3, OASL, LOC100132181, HLA-DRB4, CCL2, UGCG, PDXDC1, ALS2CR11,SCAND2, GBP4, RUNX3, LRRC8B, TSEN54, UBA7, STK4, FAM179A, TGFBR3,CCDC114, GTF2H2, AKAP9, BNC2, BZRAP1, CCL4, CHST2, CSF1, ERBB2, GBR56,GRAMD3, GRHL2, GRK4, ITIH4, KIAA1618, LOC147646, LOC150622, LOC161527,PLEKHF1, PRKD2, RGNEF, SESN2, SLAMF7, SPON2, STAT1, SYNGR1, TRX21,TMEM67, TUBE1, ZNF827, AGFG1, BTG1, CFDP1, CNPY2, FAM105A, GATM, GTF2H2,IGHG1, IL18RAP, N4BP2, PHACTR1, QK1, RTKN2, SLC16A1, SOCS1, SPAG17,ST6GALNAC1, STK17B, STT3B, STX16, TBC1D12, TRIM4, UACA, and WHAMML2,wherein the solid support consists of 1000 or fewer nucleic acid probes,wherein each nucleic acid probe comprises at least 10 nucleotides. 2.The solid support of claim 1, further comprising a plurality of nucleicacids that specifically hybridize to a plurality of endogenous referencegenes selected from the group consisting of USP7, MAPRE2, CSNK1G2,SAFB2, PRKAR2A, PI4KB, CRTC1, HADHA, MAP1LC3B, KAT5, CDC2L1, CDC2L2,GTSE1, TCF25, CHP, LRRC40, hCG 2003956, LYPLA2, LYPLA2P1, DAXX, UBE2NL,EIF1, KCMF 1, PRKRIP1, CHMP4A, TMEM184C, TINF2, PODNL1, FBXO42,LOC441258, RRP1, C10orf104, ZDHHC5, C9orf23, LRRC45, NACC1,LOC100133445, LOC115110, and PEX16.
 3. The solid support of claim 1,further comprising a plurality of nucleic acids that specificallyhybridize to a plurality of ischemic stroke-associated biomarkersselected from the group consisting of FAT3, GADL1, CXADR, RNF141,CLEC4E, TIMP2, ANKRD28, TIMM8A, PTPRD, CCRL1, FCRL4, DLX6, GABRB2, GYPA,PHTF1, CKLF, CKLF, RRAGD, CLEC4E, CKLF, FGD4, CPEB2, LOC100290882,UBXN2B, ENTPD1, BST1, LTB4R, F5, IFRD1, KIAA0319, CHMP1B, MCTP1, VNN3,AMN1, LAMP2, FCHO2, ZNF608, REM2, QKI, RBM25, FAR2, ST3GAL6, HNRNPH2,GAB1, UBR5, VAPA, MCTP1, SH3GL3, PGM5, CCDC144C, LOC100134159, LECT2,SHOX, TBX5, SPTLC3, SNIP, RBMS3, P704P, THSD4, SNRPN, GLYATL1,DKRZP434L187, OVOL2, SPIB, BXDC5, UNC5B, ASTN2, FLJ35934, CCDC144A,ALDOAP2, LDB3, LOC729222, PPFIBP1, HNRNPUL2, ELAVL2, PRTG, FOXA2, SCD5,LOC283027, LOC344595, RPL22, LOC100129488 and RPL22.
 4. The solidsupport of claim 1, further comprising a plurality of nucleic acids thatspecifically hybridize to a plurality of cardioembolic stroke-associatedbiomarkers selected from the group consisting of IRF6, ZNF254, GRM5,EXT2, AP3S2, PIK3C2B, ARHGEF5, COL13A1, PTPN20A, PTPN20B, LHFP, BANK1,HLA-DOA, EBF1, TMEM19, LHFP, FCRL1, OOEP, LRRC37A3, LOC284751, CD46,ENPP2, C19orf28, TSKS, CHURC1, ADAMTSL4, FLJ40125, CLEC18A, ARHGEF12,C16orf68, TFDP1 and GSTK1.
 5. The solid support of claim 1, furthercomprising a plurality of nucleic acids that specifically hybridize to aplurality of carotid stenosis-associated biomarkers selected from thegroup consisting of NT5E, CLASP2, GRM5, PROCR, ARHGEF5, AKR1C3, COL13A1,LHFP, RNF7, CYTH3, EBF1, RANBP10, PRS S35, C12orf42, LOC100127980,FLJ31945, LOC284751, LOC100271832, MTBP, ICAM4, SHOX2, DOPEY2, CMBL,LOC146880, SLC20A1, SLC6A19, ARHGEF12, C16orf68, GIPC2 and LOC100144603.6. The solid support of claim 1, further comprising a plurality ofnucleic acids that specifically hybridize to a plurality of atrialfibrillation-associated biomarkers selected from the group consisting ofSMC1A, SNORA68, GRLF1, SDC4, HIPK2, LOC100129034, CMTM1, TTC7A, LRRC43,MIF, SLC2A11, PER3, PPIE, COL13A1, DUSP16, LOC100129034, BRUNOL6,GPR176, C6orf164 and MAP3K7IP1.
 7. The solid support of claim 1, whereinthe solid support is a microarray.
 8. The solid support of claim 1,wherein each nucleic acid probe comprises from 10 to 50 nucleotides. 9.A kit comprising the solid support of claim
 1. 10. The kit of claim 9,further comprising buffers, salts and/or other reagents to facilitateamplification and/or detection reactions for determining the expressionlevels of ischemia biomarkers.
 11. The kit of claim 9, furthercomprising one or more reaction vessels that have aliquots of some orall of reaction components to facilitate amplification and/or detectionreactions for determining the expression levels of ischemia biomarkers.12. The kit of claim 9, further comprising sample processing cartridgesor other vessels that allow for the containment, processing and/oramplification of samples in the same vessel.